Embedded system designs all have one thing in common: a microprocessor and controller. These can be as sparse as 4-bit wide controllers with less than 1K of code space or as big as a multicore multi-GHz processing supercomputer with Gis of code space. But, modern IoT-based embedded system designs also have another typical requirement. Many designs will be mixed signals, so almost every design will include wireless communications.Herein lies a challenge. Will a designer choose an overkill all-in open processor with much more performance, peripherals, memory, and processing power than is needed just to have a single integrated processor or dedicated functional processors to handle dedicated and specific tasks?Both approaches may have merit depending on a variety of design constraints. Is time to market the driving force? Is cost the critical constraint? What about size or power efficiency? There are many factors and microcontrollers/microprocessors to choose from, especially as embedded systems invade our living space and become more prevalent. Nearly every place is now an intelligent environment.<h2>Wireless Protocols</h2>Every wireless device uses some sort of protocol to establish and maintain communications. While higher-cost, higher-end cellular protocols can be used for home and building communications, this carries the cost of a recurring monthly cellular fee. Modern 4G and 5G systems fall into this category, utilizing a range of wireless protocols for enhanced connectivity.Wi-Fi® is popular for media-based streaming and high-speed connectivity within a facility. Many Wi-Fi ICs and modules are readily available for designers in their embedded design. Still, many designs don't require the multi-Gbit/sec data rates or have higher power budgets to justify the more sophisticated and costly Wi-Fi medium.Zigbee,&nbsp;Bluetooth®, and LTE are the more power-friendly wireless protocols for room or building use. These require much less firmware, memory, and current, making them suitable for remote controls, lighting systems, media systems, temperature sensors, smoke/fire detectors, heating/cooling systems, and more.What makes these protocols even more desirable is the topological flexibility they offer. In addition to point-to-point, these protocols can offer star, mesh, peer-to-peer, and client-server architectures. Star networks require each node to be in closer proximity to the star center, which is usually an aggregator. Peer-to-peer and mesh networks can “pass the baton” from node to node and cover longer distances since packets propagate along a routing path. This can also help preserve battery life since not a lot of transmission power is needed. Eventually, packets that are necessary for connecting to the World Wide Web will need to be routed to an access point. In all cases, security should be used.<h2>Security</h2>Sometimes, a security breach can be just an annoyance, like if someone hacks into your smart TV and changes channels. Other cases can be more serious, though, such as someone hacking into a home medical system. Handling these threats can be tackled in a few ways, but the most common strategy is encryption.Many encryption algorithms and standards exist—some simple and some very complex. Wireless protocols like Zigbee and BLE have various methods of providing encryption protection. ZigBee uses 128-bit AES keys and is effective at applications layers as well as MAC layers. Bluetooth Low Energy (BLE) allows four layers of security:<ul><li>Level 1:No Security<ul><li>Used for scenarios where data confidentiality is not a concern.</li></ul></li><li>Level 2:Unauthenticated Pairing with Encryption<ul><li>Basic level of security, encrypting data transmission without verifying the identity of the connecting device.</li></ul></li><li>Level 3:Authenticated Pairing with Encryption<ul><li>Enhances security with a method of authentication, such as a PIN, before establishing an encrypted connection.</li></ul></li><li>Level 4: Authenticated LE Secure Connections<ul><li>The highest level of security in BLE, which uses an advanced encryption algorithm for authenticated pairing and secure connections.</li></ul></li></ul>Hardware-accelerated security functions can offload security functions from firmware and make processors much more desirable. Hardware encryption, decryption, hash code generation, pseudo-random sequence generators, and other blocks operate at lightning speed in hardware but take longer to implement in software. This adds latency time and requires the programmer to generate and debug more code.In addition to runtime data protection, another layer of security needs to be in place, which is called a secure boot. With secure boot, boot loader firmware is protected and locked, preventing anyone from rewriting this critical code and redirecting its functionality. Normally, unprotected firmware feeds a processor when it boots. If it is replaced in flash somehow, the system is compromised. Secure boot takes advantage of strongly encrypted initial boot instructions, which then use digital signatures to authenticate the next layer of startup code.<h2>A Dream Come True</h2>Realizing the tightrope that designers have to walk when choosing an ideal microcontroller/microprocessor, many device makers are providing microcontrollers/microprocessors targeting this massive market for IoT, building automation, automotive, and industrial control. These applications need more than a simple processor but don't need a super processor. While development time needs to be quick, cost and size are generally high on the list of constraints.One of the best ways to get the processors and peripherals you need is to use a system-on-chip (SoC) solution. These modular units can be made by an OEM for small quantity runs or used to prototype your own higher volume custom version.The key is the 64MHz&nbsp;<a href="https://www.mouser.com/new/microchip/microchip-pic32cx-advanced-security-mcus/" target="_blank">PIC32CX-BZ3</a> family of processors based on the 32-bit Cortex MF4 Arm. This processor brings a multitude of peripherals and its secure boot ROM checks integrity and authenticity before executing to ensure system root trust. There are also eight protected memory zones and a final fuse that makes it impenetrable.The WBZ351 (Figure 1) drives the <a href="https://www.mouser.com/new/microchip/microchip-pic32x-bz3-wbz351-modules/" target="_blank">WBZ35x modules</a>, which feature a fully compliant Bluetooth Low Energy 5.2 transceiver. The transceiver is also Zigbee 3.0 certified with software stacks built around the robust MPLAB Harmony v3 framework.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728876602476-WBZ351+Power+Module+Block+Diagram.webp" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: The peripheral-packed WBZ351 requires few external devices to implement the entire IoT or wireless design. (Source: Microchip Technology)Also important are the hardware-based security accelerator and public critical hardware (Figure 2). The AES security encryption and HASH code generator are also included to create a secure execution environment. Anti-rollback and firmware readable life cycle encounters offer even more levels of protection.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728876638327-WBZ35x+Module+Block+Diagram.webp" style="width: 100%px;" class="fr-fic fr-dib">Figure 2: The WBZ351 module contains all the processing horsepower and peripherals needed to support smart homes and buildings, industrial control and monitoring, and wireless IoT applications. (Source: Microchip Technology)<h2 id="isPasted">Conclusion</h2>When it comes to the IoT and smart environments, designers have a big job. They must integrate wireless connectivity with strict security measures. That’s where Bluetooth Low Energy and Zigbee come in. These solutions can cover large areas with mesh networks while consuming less power. By incorporating secure boot and capacitive touch functionalities, designers can accelerate concept-to-market and allow designers to meet the demands for security and user interaction in today’s IoT devices.The PIC32CX-BZ3 family of processors packs everything needed into one place, including advanced connectivity options and hardware-based security features. By leveraging powerful solutions, designers can navigate complex modern IoT ecosystems to ensure smart environments are intelligent, secure, and user-friendly.

When it comes to the IoT and smart environments, designers have a big job. They must integrate wireless connectivity with strict security measures. 

Wireless IoT Designs Just Got Easier

Most modern Internet-of-Things appliances and devices can be monitored, controlled and activated from anywhere in the world. These things generate data regularly,&nbsp;and collectively they account for a massive amount of data. To access information and services quickly and reliably, companies across all sectors are more invested in connectivity, which entails faster, more reliable networks and better encryption and security.Smart cities have the potential to better people’s lives by bridging the gap between the connected consumer and a connected infrastructure. Imagine a world where you save time getting to your flight because an application in your cellphone let you know of an open parking spot on level 4, or if traffic lights could more dynamically control traffic flow to ease commutes. Imagine if a connected lighting pole in front of your house could communicate with the utility company when the lights go out.Connectivity is a key part of making this a reality.Utilities and companies developing products for smart cities have several connectivity options, and the Wi-SUN field area network (FAN) is a good option. Why? Let’s start by considering its reliability.Most common network topologies are star or mesh (shown in <a href="https://www.ti.com/document-viewer/lit/html/sszt224?keyMatch=wireless%20connectivity#R_DOCUMENT-HEADER1_FIG1" data-di-id="di-id-d6fb6dc7-f2bdb606" target="_blank">Figure 1</a>); Wi-SUN is a mesh network.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728285513761-GUID-3EFD7940-459B-4C51-BC94-BB8C2D12EA0A-low.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 1 Example of mesh and star networksThe star topology is simple and easy to configure, having a hierarchical structure, where bridges and switches are normally connected to a small number of end nodes. Because of its structure, it can have a single point of failure, which may cause concerns when a field crew must perform maintenance or replace a malfunctioning device to keep the network up and running.A mesh topology is not a hierarchical structure, and as such, you can add routers dynamically to the network to extend the range of a node, using self-configuration to connect to other routers. In the event of a router failure, the network will go into “self-healing” mode, during which the routers find another available connection to allow traffic to continue. What does that mean for end users? A more robust network and reduced downtime for the thousands of connected nodes.Wi-SUN is based on a frequency-hopping scheme, which contributes to its robustness and reliability because it reduces potential packet losses caused by interference from other networks, especially in high-density areas like city downtowns (shown in <a href="https://www.ti.com/document-viewer/lit/html/sszt224?keyMatch=wireless%20connectivity#R_DOCUMENT-HEADER1_FIG2" data-di-id="di-id-ee77b11a-499d32a" target="_blank">Figure 2</a>). Frequency hopping also makes it possible to transmit high-output power in Canada and in the Americas, up to +30 dBm.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728285532756-GUID-4F64B902-0E17-4C7E-8D0F-D3BF7808E1BC-low.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 2 Example of how frequency-hopping can avoid interferenceWi-SUN supports a range of data rates, trading off coverage versus throughput. This enables the Wi-SUN FAN to meet the needs of a wide range of network deployment applications, like electric vehicle charging stations, smart transportation, smart parking, environmental sensors and traffic management (<a href="https://www.ti.com/document-viewer/lit/html/sszt224?keyMatch=wireless%20connectivity#R_DOCUMENT-HEADER1_FIG3" data-di-id="di-id-9d147ffe-6cb3c431" target="_blank" id="isPasted">Figure 3</a>). Consider the smart city example – throughput and coverage needs can vary widely among certain applications. Smart meters and smart parking, for example, have a need to transmit different amounts of data. The Wi-SUN FAN can scale as needed to meet these varied demands, enabling the applications illustrated below.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728285551351-GUID-3D6F6448-2D9D-4A18-B2AA-52D864BA34C3-low.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 3 Example of potential applications using the Wi-SUN FANAnother concern that Wi-SUN addresses is security. Hackers are sharpening their skills by the minute, and networks must be resilient against potential threats designed to steal data. Wi-SUN has a security profile that uses device certificates authenticated by trusted root certification authorities to prevent unauthorized network access. It also uses cryptoalgorithms such as elliptic curve Diffie-Hellman, elliptic curve digital signature algorithm and Advanced Encryption Standard-128 cipher block chaining-message authentication code to preserve message confidentiality and integrity. This is important when adding new devices to the network and enabling their identification and authentication. Wi-SUN equipment manufacturers can even obtain a cybersecurity certificate indicating compliance with the FAN Technical Profile Specification.Because Wi-SUN provides scalability reliability, security and high speed, you may be wondering if it is costly. The good news is that Wi-SUN is an open-standard solution, based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4g wireless standard. As an open standard, it allows the interoperability of equipment from different manufacturers, which may translate to competitive prices for consumers. To guarantee compatibility, manufacturers must go through a formal certification process, which should give city managers and utility companies peace of mind.As of this month, there are more than 230 members of the Wi-SUN alliance representing 26 countries, with more than 96 million devices deployed worldwide.Texas Instruments provides transceivers and network processors that support Wi-SUN FAN 1.0. For example, the low-power and high-performance <a href="https://www.ti.com/product/CC1200" target="_blank" data-di-id="di-id-aca99eaa-a03fa6f8">CC1200</a> wireless transceiver supports a maximum transmission data rate of 1 Mbps and has a sensitivity of -122 dBm at 1.2 kbps, which translates to high speed and long range. It also meets North American, European and Japanese standards.For developers looking for a network processor, <a href="https://www.ti.com/product/CC1312R" target="_blank" data-di-id="di-id-479cf99c-d47db8bb">CC1312R</a> and <a href="https://www.ti.com/product/CC1352P" target="_blank" data-di-id="di-id-479cf99c-2279ca15">CC1352P</a> wireless microcontrollers include a 48-MHz Arm® Cortex® M4F, with flash memory (so you can update your firmware over the air) and a cryptoaccelerator for security purposes. Block diagram shown in <a href="https://www.ti.com/document-viewer/lit/html/sszt224?keyMatch=wireless%20connectivity#R_LEADING_INDUSTRY_CONNECTIVITY_AS_A_WI-SUN_ALLIANCE_PROMOTER_MEMBE_FIG1" data-di-id="di-id-effaa648-b73565f1" target="_blank">Figure 4</a> below.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728285585273-GUID-0CC59979-23D9-45DD-9B1F-DF489DD4B4F9-low.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 4 CC13x2 Block DiagramWi-SUN brings these benefits to utilities, equipment manufacturers and end users:<ul><li>A robust network with low downtime due its mesh configuration.</li><li>A reliable communication technology that uses frequency-hopping scheme, resulting in a very low number of packet losses in noisy and high-density areas.</li><li>A secure network through a well-defined security profile.</li></ul><hr><h2>Additional resources</h2><ul><li>Check out our&nbsp;<a href="https://training.ti.com/wi-sun-connected-lights-demo-smart-cities" target="_blank" data-di-id="di-id-f84d052b-a737642a">demo video</a> exploring the benefits of a Wi-SUN mesh network.</li><li>Learn about&nbsp;<a href="https://www.wi-sun.org/wp-content/uploads/Wi-SUN-Alliance-Fact-Sheet.pdf" target="_blank" data-di-id="di-id-1a43033b-4aa5aee6" data-lf-fd-inspected-kn9eq4roawkarlvp="true">Wi-SUN FAN certification program</a>.</li><li>Explore&nbsp;<a href="https://wi-sun.org/cyber-security-certificates/" target="_blank" data-di-id="di-id-e0bdc1fa-5eea0d1">cybersecurity certification</a>.</li><li>Request information about the&nbsp;<a href="https://www.ti.com/licreg/docs/swlicexportcontrol.tsp?form_id=324287&prod_no=WISUN-STACK&ref_url=epd_connect_sub1ghz%20" target="_blank" data-di-id="di-id-dc31faa5-5043dcf9">software TI provides for WI-SUN projects</a>.</li></ul>

To access information and services quickly and reliably, companies across all sectors are more invested in connectivity, which entails faster, more reliable networks and better encryption and security.

How Wi-SUN FAN Improves Connected Infrastructures

Supplementary information related to <a href="https://article.murata.com/en-eu/article/multiplexing-and-multiple-access-1" target="_blank">FDMA, TDMA, and CDMA Multiple Access (1)</a> is presented below.<h2>&lt; Column &gt; How Multiplexing Works: FDM, TDM, and CDM</h2>A number of types of multiplexing are used for wireless communication, and the following are some of the most common:• Frequency-division multiplexing (FDM) • Time-division multiplexing (TDM) • Code-division multiplexing (CDM)Figures 7-1, 7-2, and 7-3 are conceptual diagrams of these multiplexing techniques, with a focus on the transmission path portions enclosed in red dashed lines.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1722839179083-img0012-en.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 7-1: Conceptual Diagram of Frequency-Division Multiplexing (FDM)<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1722839190979-img0013-en.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 7-2: Conceptual Diagram of Time-Division Multiplexing (TDM)<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1722839204356-img0014-en.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 7-3: Conceptual Diagram of Code-Division Multiplexing (CDM)<h3 id="isPasted">Frequency-Division Multiplexing (FDM)</h3>Frequency-division multiplexing (FDM) is a multiplexing technology that assigns multiple data streams to different frequency bands, and transmits the frequency bands as channels simultaneously via a single transmission path.Figure 7-1 shows a general conceptual diagram of FDM. On the sending side, the frequency bands assigned to the multiple data streams are treated as channels, which are sent via a single transmission path using multiplexing. On the receiving side, the transmitted data streams are extracted by devices capable of selecting specific frequency bands. An example of the use of FDM for wireless communication is terrestrial digital television broadcasting in Japan. There is a single transmission path, the air, and signals containing image and audio data are broadcast from multiple television stations on different frequencies. On the receiving side, the user can view TV shows of their choice by selecting specific frequencies. FDM is also used for analog radio broadcasting.<h3>Time-Division Multiplexing (TDM)</h3>Time-division multiplexing (TDM) is a multiplexing technology that divides up multiple data streams into time intervals assigned as channels, and transmits them on the same frequency via a single transmission path.Figure 7-2 shows a general conceptual diagram of TDM. On the sending side, multiple data streams from a device are divided into time slots and assigned to channels, which are sent via a single transmission path using multiplexing. On the receiving side, by dividing up the channels using the same timing as the sending, the transmitted data can be received by multiple devices. An example of the use of TDM for wireless communication is television broadcasting in Europe and North America.<h3>Code-Division Multiplexing (CDM)</h3>Code-division multiplexing (CDM) is a multiplexing technology that mixes with the data unique identifier codes for each device, combines the signals in a single frequency band, and then transmits the combined signals simultaneously via a single transmission path.Figure 7-3 shows how CDM works. The data is mixed (modulated) with periodic identifier codes that have a duration shorter than that of one bit of data to generate a modulated signal.*8 The multiple modulated signals from each device are added together as is, multiplexing them, and the multiplexed signals are sent via a single transmission path. On the receiving side, each device mixes in with the multiplexed signals the identifier codes used for modulation to restore (demodulate) the data and extract the transmitted data.&nbsp; There are no examples of the use of CDM as a standard for wireless communication, but adoption of the related multiple access scheme called code-division multiple access (CDMA) is widespread.*8 During transmission, the frequency bandwidth of the modulated signal ends up being wider than that of the original data stream (original signal). This characteristic provides advantages for communication applications, such as greater tolerance for external noise impinging on the transmission path.<h2>&lt; Column &gt; Explanation of the Terms FDD-LTE and TD-LTE Found in Smartphone Technical Specifications</h2>Sending and receiving take place simultaneously during mobile communications on smartphones or flip phones and phone calls on landline telephones, with a single channel being used for bidirectional transmission of audio data. Such bidirectional transmission can also be thought of as a type of multiplexing technology.Terms such as “FDD-LTE” and “TD-LTE” (TDD-LTE is typically shortened to TD-LTE) often appear in the technical specifications of products such as smartphones. FDD stands for “frequency-division duplex” and TDD stands for “time-division duplex,”*9 both of which refer to bidirectional transmission.&nbsp; Long-term evolution (LTE), on the other hand, is the telecommunications standard of the 4th generation mobile communication system (4G), and this also includes multiple access (OFDMA in the case of 4G). Therefore, “FDD-LTE” indicates both bidirectional transmission and the multiple access scheme used.&nbsp; It is somewhat complicated, but bidirectional transmission is not equivalent to multiplexing, so it is typical when writing about multiple access, which utilizes both bidirectional transmission and multiplexing, to mention the two separately.*9 FDD stands for “frequency-division duplex,” in which different frequencies are assigned to downloading (receiving of data by the device) and uploading (sending of data by the device) in order to implement bidirectional transmission (Figure 8-1). On the other hand, TDD stands for “time-division duplex,” in which the same frequency band is used for both downloading and uploading, the audio data is split up along the time axis, and sending and receiving of voice data alternates at very short intervals (on the order of milliseconds in the case of voice calls) in order to implement bidirectional transmission (Figure 8-2). Thus, strictly speaking, TDD does not provide simultaneous sending and receiving, although this results in no unnatural audible effects in the case of voice calls. Bidirectional transmission is explained in more detail at <a href="https://article.murata.com/en-eu/article/basics-of-wireless-communication-2" target="_blank">Basic Knowledge of Wireless Communication: Wireless Mechanism (2)</a>.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1722839230983-img0015-en.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 8-1: Conceptual Diagram of Frequency-Division Duplex (FDD)<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1722839242889-img0016-en.png" style="width: 100%px;" class="fr-fic fr-dib">Figure 8-2: Conceptual Diagram of Time-Division Duplex (TDD)

Supplementary information related to FDMA, TDMA, and CDMA Multiple Access (1) is presented below.

FDMA, TDMA, and CDMA Multiple Access: Effective Utilization of Signals (Bandwidth) in Wireless Communication (2)

Optimizing Network Design and Performance through Strategic Hardware Selection


Navigating Network Infrastructure: Patch Panel vs Switch

Connectivity, though often underestimated, plays a pivotal role in the success of IoT projects. In our recent webinar, <a href="https://www.wevolver.com/article/steering-iot-innovation-in-global-asset-expeditions-and-fleet-journeys" target="_blank" rel="noopener noreferrer">Unlocking Continuous Connectivity with Particle's M-Series Products,</a>&nbsp; Colleen Lavin, the Developer Success Lead at Particle, gave a comprehensive introduction to the M-Series and how to increase your IoT project connectivity.Watch the full webinar in the video above, or read on to get an overview of the highlights.&nbsp;<h1 dir="ltr">Challenges of Wireless Connectivity</h1><ol><li dir="ltr">Environment-Specific Technologies:<ul><li dir="ltr">There is no single wireless technology that guarantees connectivity everywhere. Colleen explains, "Connectivity is actually really complex. There's not a single wireless technology that works everywhere."</li><li dir="ltr">Home or single-location Wi-Fi is straightforward, but mobility introduces complexity. As Colleen notes, "Wi-Fi connectivity is the easiest. However, as soon as you add any level of mobility into that, it becomes a little bit more complex."</li></ul></li><li dir="ltr">Hospital and Academic Settings:<ul><li dir="ltr">Hospitals and academic buildings are prime examples where connectivity can be challenging. Colleen highlights, "I don't know if you've been to a lot of hospitals lately, or academic buildings. But there's always at least one corner of the hospital or the building where cell phones go to die."</li><li dir="ltr">Despite efforts, there are often areas within these buildings where cellular signals are weak or nonexistent. This phenomenon creates significant issues, especially in critical environments like hospitals where seamless communication is vital.</li></ul></li><li dir="ltr">The Myth of Universal Cellular Connectivity:<ul><li dir="ltr">Relying solely on cellular connections is not always viable. Colleen remarks, "You can use the hospital example and just say, 'Oh, well, if they want a hundred percent connectivity, you should make sure that they have cellular connection.' However, that's not always practical."</li><li dir="ltr">Many buildings have dead zones where cellular devices lose signal, reminiscent of a pre-cellular era. This can be frustrating and disruptive, especially in professional and academic settings where reliable connectivity is essential.</li></ul></li></ol><h1 dir="ltr">The M-Series and Particle</h1>During the webinar, Colleen provided an in-depth look at the <a href="https://www.particle.io/blog/connect-anywhere-introducing-the-m-series/" target="_blank" rel="noopener noreferrer">M-Series and Particle</a>.<ul><li dir="ltr">M-Series: The M-Series represents a new generation of modular connectivity solutions. These devices are designed to be flexible, supporting multiple wireless standards and adapting to various environments. Colleen emphasized the importance of modularity, saying, "The M-Series allows us to tailor connectivity solutions to specific needs, ensuring optimal performance regardless of the environment."</li><li dir="ltr">Particle:&nbsp;Particle is a comprehensive IoT platform that integrates hardware and software to provide seamless connectivity for devices. Colleen described Particle as "a game-changer for IoT deployments," noting that it simplifies the process of connecting devices to the cloud and managing them remotely. The platform supports a range of connectivity options, including Wi-Fi, cellular, and mesh networks, making it versatile for different applications.</li></ul><h1 dir="ltr">Conclusion</h1>Ensuring consistent and reliable connectivity is a complex but critical task. It requires understanding the unique challenges of each environment and implementing tailored solutions to mitigate connectivity issues. Colleen's insights, combined with the capabilities of the M Series and Particle, underscore the importance of proactively addressing these challenges to ensure the success of IoT projects and operations. As technology continues to evolve, focusing on overcoming connectivity hurdles will be essential for progress and efficiency in all sectors.We invite you to watch the complete webinar to gain a more in-depth understanding and hear Colleen's full insights.&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/749NVka7ksQ?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>Check out the latest articles from Particle here:<a href="https://www.wevolver.com/article/connecting-the-future-bridging-the-digital-divide-in-intelligent-cities-and-underserved-regions" target="_blank">Connecting the Future: Bridging the Digital Divide in Intelligent Cities and Underserved Regions</a><a href="https://www.wevolver.com/article/bridges-to-the-future-revolutionizing-remote-infrastructure-management-with-iot" target="_blank">Bridges to the Future: Revolutionizing Remote Infrastructure Management with IoT</a><a href="https://www.wevolver.com/article/tech-for-the-planet-iot-innovations-in-environmental-monitoring-and-disaster-management" target="_blank">Tech for the Planet: IoT Innovations in Environmental Monitoring and Disaster Management</a><a href="https://www.wevolver.com/article/unearthing-the-potential-of-precision-agriculture" target="_blank">Unearthing the Potential of Precision Agriculture</a><a href="https://www.wevolver.com/article/steering-iot-innovation-in-global-asset-expeditions-and-fleet-journeys" target="_blank" rel="noopener noreferrer">Steering IoT Innovation in Global Asset Expeditions and Fleet Journeys</a>

Ensuring Connectivity in Complex Environments


Unlocking Continuous Connectivity with Particle's M-Series Products: Webinar Wrap-Up

<h2 id="isPasted">Essential Technologies that Enable Effective Utilization of Signal Bandwidth for Wireless Communication</h2>Everyday our smartphones transmit and receive audio, images, videos and other data. While many people are using the same signal band at the same time, transferring huge amounts of data, we have come to think this is perfectly normal. This is possible thanks to technologies that prevent problems when sending and receiving different types of data, such as the overlapping of data or interference from noise. This article uses graphical illustrations to describe two such technologies aimed at enabling efficient utilization of frequency bandwidth (or bandwidth for short),*1 which is to say the efficient utilization of radio signals:&nbsp; • “multiplexing,” which allows multiple data streams to be transferred at the same time, and&nbsp; • “multiple access,” which makes use of multiplexing technology to allow simultaneous connections with multiple users.Note that multiple access (also called “multiaccess”) is an important technique contributing to the 5th Generation Mobile Communication System (5G), which aims to support very large numbers of simultaneous connections (1 million connections per square kilometer), including connections to “things” such as home appliances and IoT devices.*1 The wider the frequency bandwidth (bandwidth) used for wireless communication, the higher the data communication speed (transmission speed). We plan to explain the relationship between frequency bandwidth and transmission speed in another article.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMjMyMjgxLWltZzAwMDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Multiple users (devices) using mobile communications at the same time (illustrative photo)<h2 id="isPasted">Transmission of Multiple Data Streams by Wireless Communication</h2><h3>Multiplexing: Effective Utilization of a Single Transmission Path (Air)</h3>The basic model of a communication system, whether using wired or wireless communication,*2 can be represented as shown in Figure 1 (<a href="https://article.murata.com/en-eu/article/basics-of-wireless-communication-1" target="_blank">Basic Knowledge of Wireless Communication: Wireless Mechanism (1)</a>). In this model, the sending side, transmission path, and receiving side are conceived of as one unit, and the stream of data transmitted at a particular time is conceived of as one unit. (We will refer to this as “simple communication” for the time being.) Now, if the sender could send multiple streams of data to the receiving side simultaneously, the efficiency of data sending and receiving would increase. This is what led to the idea of transmitting multiple streams of data simultaneously over a single transmission path. This technology is called multiplexing.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMjUzMjE4LWltZzAwMDItZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: Configuration of Basic Model for Communication Systems*2 Generally speaking, the transmission path of a communication system is either cables or air, and such systems are classified as either wired or wireless communication based on the transmission path used for telecommunication.<h3>Multiple Access: Implementing Wireless Communication among Multiple Users without Interference</h3>If we think of multiplexing as sending multiple streams of data at the same time, superimposed on each other, we can say that for multiplexing the elements of sending side and receiving side do not exist. In the case of wireless communication, the element of “transceiving” (sending and receiving combined) can be added to multiplexing to allow multiple users to share a single transmission path to transmit multiple streams of data at the same time. This is called multiple access.*3Table 1 shows the relationship between multiplexing and multiple access. To enable comparison with multiple access, we will say that multiplexing uses one sending side and one receiving side. Also, since multiplexing has multiple channels*4 and multiple access also has multiple channels, we can say that multiple access is based on multiplexing.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMjc4OTEwLWltZzAwMDMtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Table 1: Relationship between Multiplexing and Multiple Access*3 In communication-related books and documents, as well as website content, multiplexing and multiple access are sometimes referred to without distinction, depending on what is being described. In the present article, multiple access is described as a technique that makes use of multiplexing to allow multiple users to share a transmission path to send and receive data.*4 Channel: As used here, this can be thought of simply as a route (communication path) along which a radio signal waveform carrying a single data stream travels. The term channel is used in this sense to refer to a signal line. In the case of wireless communication, one can describe a case in which 10 different signal waveforms are transmitted (multiplex transmission) as a communication path with 10 channels, for example.In actual wireless communication, rather than cases where a transmission path is being shared to transmit data from one user to another user, or from one user to multiple other users, cases where multiple users of a mobile communication system (Figure 2) or satellite communication system (Figure 3) share a transmission path are more common. Therefore, the discussion that follows focuses on the workings of multiple access. Multiplexing is explained in <a href="https://article.murata.com/en-eu/article/multiplexing-and-multiple-access-2#section-61975" target="_blank">&lt; Column &gt; How Multiplexing Works: FDM, TDM, and CDM</a>.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMjk5MDA4LWltZzAwMDQtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 2: Conceptual Diagram of Mobile Communication System<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMzE0ODE3LWltZzAwMDUtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 3: Conceptual Diagram of Satellite Communication System<h2 id="isPasted">How Multiple Access Works: FDMA, TDMA, and CDMA</h2>As we mentioned in the preceding section, multiple access is a technique that enables multiple users to communicate without interference by sharing multiplexed channels. The basic types of multiple access, from the least to the most advanced, are as follows: • Frequency-division multiple access (FDMA) • Time-division multiple access (TDMA) • Code-division multiple access (CDMA) Below we explain how each of these work, using conceptual diagrams of each type of multiple access and conceptual diagrams based on Figure 3 using satellite communication as an example.*5*5 Recent wireless communication standards, such as 4G-LTE mobile communication or Wi-Fi 6/6E and Wi-Fi 7 personal communication, use a scheme called orthogonal frequency-division multiple access (OFDMA) that is based on modulation and multiplexing technology called orthogonal frequency-division multiplexing (OFDM).An explanation of OFDM is omitted here because it would require a background knowledge of complex subjects such as data multivaluation, quadrature amplitude modulation (QAM), and the orthogonal properties of data signals on frequency spectra. We plan to cover this subject in another article.<h3>Frequency-Division Multiple Access (FDMA)</h3>FDMA divides up data streams from multiple users and assigns them to channels using different frequency bands, all of which share a single transmission path (Figure 4-1). Adoption of FDMA began in the 1980s, and it was used to carry cellphone and car phone calls under the analog 1st generation mobile communication system (1G).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMzM1NzgzLWltZzAwMDYtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 4-1: Conceptual Diagram of Frequency-Division Multiple Access (FDMA)Figure 4-2 shows a conceptual diagram of the use of FDMA for satellite communication. Figure 4-2 shows an arrangement based on Figure 3 in which one sending side (earth station E0) and multiple receiving sides (earth stations E1 to E3) are used to transmit multiplexed data signals. The data signal from earth station E0, consisting of data streams targeted at earth stations E1 to E3, modulated and assigned to different frequencies arranged at equally spaced intervals within the bandwidth supported by the satellite relay, is sent in a manner that ensures that the adjacent signal frequency bands do not overlap (to prevent interference). When earth stations E1 to E3 receive these signals, they are divided up according to the frequency each station is able to receive, and the data streams are extracted.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMzU5NDg5LWltZzAwMDctZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 4-2: Example of Satellite Communication Using Frequency-Division Multiple Access (FDMA)<h3 id="isPasted">Time-Division Multiple Access (TDMA)</h3>TDMA divides up data streams from multiple users into uniform time intervals and assigns them to channels, all of which share a single transmission path (Figure 5-1). Adoption of TDMA began in the 1990s, and it was used to carry mobile phone calls (GSM, PDC, PHS, etc.) under the digital 2nd generation mobile communication system (2G).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwMzc3MDE1LWltZzAwMDgtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 5-1: Conceptual Diagram of Time-Division Multiple Access (TDMA)Figure 5-2 shows a conceptual diagram of the use of TDMA for satellite communication. As in the preceding section, Figure 5-2 shows an arrangement based on Figure 3 in which one sending side (earth station E0) and multiple receiving sides (earth stations E1 to E3) are used to transmit multiplexed data signals.&nbsp; The data signal is sent from earth station E0, delimited by time frames and consisting of “slots” used as channels, excluding the standard burst signal*6 embedded in each frame, and each channel is assigned one of the data streams targeted at earth stations E1 to E3. Then, at each earth station from E1 to E3 the signal is divided up in a manner synchronized with the transmission timing of earth station E0, and the data streams are extracted.*6 Note that TDMA was adopted for satellite communication in addition to FDMA from around 1985.*6 To ensure stability and prevent interference with communication, TDMA requires that the channel switching speed, etc., be synchronized between the sending side and receiving side. Earth station E0 inserts a signal called a burst at the beginning of each frame for synchronization control.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwNDEwNzI0LWltZzAwMDktZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 5-2: Example of Satellite Communication Using Time-Division Multiple Access (TDMA)<h3 id="isPasted">Code-Division Multiple Access (CDMA)</h3>CDMA generates signals in which the data streams of users are mixed with unique identifier codes, and the signals of all the users are overlaid within the same frequency band and conveyed via a single transmission path (Figure 6-1). CDMA is used to carry mobile phone calls under the 3rd generation mobile communication system (3G) introduced in the 2000s.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwNDI5MzM4LWltZzAwMTAtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 6-1: Conceptual Diagram of Code-Division Multiple Access (CDMA)Figure 6-2 shows a conceptual diagram of the use of CDMA for satellite communication. As in the preceding section, Figure 6-2 shows an arrangement based on Figure 3 in which one sending side (earth station E0) and multiple receiving sides (earth stations E1 to E3) are used to transmit multiplexed data signals.Earth station E0 mixes the identifier codes assigned to earth stations E1 to E3 on the receiving side with the data signals targeted at each earth station, generating signals with frequency bands wider than that of the original data signals, and adds them together to create a multiplexed signal that it sends to the satellite relay. Earth stations E1 to E3 each receive the multiplexed signals from the satellite relay, mix in the earth station identifier codes to divide up the signals, and extract data only from the signal that matches their own identifier code. Note that adoption of CDMA for satellite communication began in the 1990s.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzIyMjIwNDQ5Njc0LWltZzAwMTEtZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 6-2: Example of Satellite Communication Using Code-Division Multiple Access (CDMA)<h2 id="isPasted">Summary</h2>As we have seen, multiple access is an important technique for wireless communication, from the aspect of enabling wireless communication among multiple users without interference. Now we would like to delve into a little more detail before concluding this article.&nbsp; Multiple access schemes have become more advanced over time, evolving from FDMA to TDMA to CDMA, but it is no exaggeration to say that the increased frequency utilization efficiency*7 accompanying these advances has been a key aspect of the development of wireless communication. For example, achieving better frequency utilization efficiency in mobile communications makes it possible to increase both the number of users and the overall volume of data that can be transmitted.&nbsp; This is touched on briefly in this article, but the multiple access scheme used by 4G, the most widely used mobile communications system at present, is orthogonal frequency-division multiple access (OFDMA), which is said to provide twice the frequency utilization efficiency of 3G using CDMA. In turn, 5G uses non-orthogonal multiple access (NOMA), which delivers even better frequency utilization efficiency than OFDMA.&nbsp; So, to repeat, multiple access, which has advanced with the aim of increasing frequency utilization efficiency, can be considered indispensable to future developments in wireless communication as well as expanded adoption.*7 Frequency utilization efficiency: As used here, this can be simply be understood as the data transmission speed (in units of bits per second (bps)/Hz) per unit of frequency bandwidth. Note that frequency utilization efficiency is sometimes referred to as spectrum efficiency or bandwidth efficiency.

Everyday our smartphones transmit and receive audio, images, videos and other data. While many people are using the same signal band at the same time, transferring huge amounts of data, we have come to think this is perfectly normal.

FDMA, TDMA, and CDMA Multiple Access: Effective Utilization of Signals (Bandwidth) in Wireless Communication

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Explore the future of connected communities in intelligent cities and underserved regions, highlighting the role of technologies like 5G, AI, and blockchain in enhancing connectivity and promoting inclusive development.

Connecting the Future: Bridging the Digital Divide in Intelligent Cities and Underserved Regions

IoT devices&nbsp;capable of&nbsp;providing fast and power-efficient location details are in high demand, and nowhere more so than in the $9 trillion global logistics and transportation sector[1].&nbsp;Driven by&nbsp;an e-commerce boom and a shift in consumer preference&nbsp;towards online purchases,&nbsp;logistics&nbsp;companies are&nbsp;shipping&nbsp;a staggering volume of parcels. The biggest e-commerce company of the lot, Amazon, processed 4.79 billion U.S.&nbsp;delivery&nbsp;orders in 2022,&nbsp;equivalent&nbsp;to 13.13 million a&nbsp;day[2].While not every delivery is tracked in ‘real time’ at the parcel level yet, that day will come, particularly for high value or perishable cargoes. As such, logistics companies looking to improve efficiencies and reduce costs are rapidly adopting cellular IoT and Wi-Fi solutions that support real time location.&nbsp;&nbsp;<h2>Cellular IoT and GNSS&nbsp;deliver&nbsp;RTLS</h2>To provide real time location, such an IoT device can employ cellular IoT wireless connectivity in concert with GNSS capability—for example Nordic Semiconductor’s&nbsp;<a href="https://www.nordicsemi.com/Products/Wireless/Low-power-cellular-IoT/Products?lang=en#infotabs" target="_blank">nRF91 Series</a>&nbsp;SiPs—which is generally accurate enough (within 10 meters) for many asset tracking applications.&nbsp;&nbsp;GNSS alone, however, is far from perfect. It won’t work indoors, and even outdoors the relatively weak signal can easily be disrupted by tall buildings, as well as other radio sources. Another challenge for GNSS-based asset tracking is the time it can take to secure a fix, and the battery drain that causes on an already resource-constrained device.&nbsp;<h2>Location and&nbsp;low-power</h2>One solution to the issue of battery drain is to use Assisted- and Predicted-GPS (A-GPS and P-GPS), that employ satellite assistance data stored in a Cloud database, relayed to the IoT device via an LTE-M or NB-IoT network, saving significant power compared to an extended first fix. Another option is to use the known location of cellular base stations to narrow down the position of the receiver. Single-cell (SCELL) and multi-cell (MCELL) location methods rely on identifying in which cell the tracked device is situated, and then referencing the cell ID against a database of known base station locations.&nbsp;&nbsp;A further locationing technique which complements cellular IoT and GNSS is Wi-Fi Service Set Identifier (SSID) scanning. Every Wi-Fi access point network is identified with an SSID, and with knowledge of the SSID, it’s possible to cross reference against Cloud databases to approximately locate the position of an IoT device.&nbsp;&nbsp;<h2>The power of Cloud&nbsp;services</h2>To take advantage of these various locationing technologies, IoT asset tracking devices require not only LTE-M and NB-IoT cellular connectivity and GNSS, but also Wi-Fi (if using SSID locationing), and the Cloud services to support them.&nbsp;&nbsp;This is why Nordic Semiconductor has backed its cellular IoT hardware offering—the nRF91 Series SiPs—and it’s Wi-Fi solutions—the&nbsp;<a href="https://www.nordicsemi.com/Products/Wireless/WiFi/Products?lang=en#infotabs" target="_blank">nRF70 Series</a>&nbsp;Companion ICs—with&nbsp;<a href="https://nrfcloud.com/?__hstc=8439722.02bd342c1db7d9a6a838dac1f5f506c2.1719564172438.1719564172438.1719564172438.1&__hssc=8439722.3.1719564172438&__hsfp=3048804036#/" target="_blank">nRF Cloud</a>&nbsp;and&nbsp;<a href="https://www.nordicsemi.com/Products/Cloud-services" target="_blank">Cloud Services</a>. By providing hardware, software, and Cloud services, Nordic offers a complete solution.&nbsp;&nbsp;For real time asset tracking, Nordic’s&nbsp;<a href="https://www.nordicsemi.com/Products/Cloud-services/Location-Services?lang=en#infotabs" target="_blank">Cloud Location Services</a>&nbsp;can be used to assist devices and customer applications that need SCELL, MCELL, A-GPS, P-GPS and/or Wi-Fi location features, guaranteeing they will last longer in the field while also sending accurate location data to the Cloud. These features can all be implemented in the same device and used when needed, depending on accuracy requirements at any given time.&nbsp;&nbsp;For example, if you want to track an asset moving between two locations, precise location is likely not needed, as long as it can be determined that the asset is moving towards the destination. That means an asset tracker powered by an nR91 Series SiP can use SCELL or MCELL location, while also ensuring minimal power consumption.&nbsp;&nbsp;As the asset gets closer to delivery, more precise location data might be necessary, at which point Nordic’s Cloud Location Services can dynamically enable GNSS-based location or even Wi-Fi location (assuming the asset tracker employs Wi-Fi), to determine a more precise location and track the asset all the way to its destination.&nbsp;&nbsp;<h2>Cloud-based security services</h2>In addition to location support, these devices also need security credentials to connect to the Cloud. Securely provisioning devices can be complex and costly, and typically involves creating proprietary infrastructure and processes. Nordic’s Cloud Security Services solve these problems by providing a secure and unique identity for devices that can be used for authentication with Nordic Root of Trust, as well as secure provisioning to configure devices remotely with the required credentials.&nbsp;For the developer this means they can ensure only authentic Nordic devices are used in their supply chain, and that their application firmware only runs on authentic Nordic silicon. It also protects against counterfeiting and cloning, and verifies the devices are what they claim to be, before they connect to the Cloud.&nbsp;&nbsp;This combination of Cloud location and security services will spur more innovative applications by relieving companies of the burden of managing and integrating their devices, allowing them to focus their efforts on developing new and innovative solutions.&nbsp;<hr><h3>References</h3>1. Logistics Market Size and Growth 2024 to 2033. Precedence Research, June 2024.&nbsp; 2. Amazon Logistics Statistics. CapitalOne Shopping Research, October 2023.&nbsp;

While not every delivery is tracked in ‘real time’ at the parcel level yet, that day will come, particularly for high value or perishable cargoes. Logistics companies looking to improve efficiencies and reduce costs are rapidly adopting cellular IoT and WiFi solutions that support real time location

The Power of Cloud Services

Wireless connectivity makes dumb&nbsp;products intelligent. Smart devices can transmit information about their surroundings and conditions while receiving instructions and updates. That in turn enables functionality that’s impossible for products operating in isolation.&nbsp;&nbsp;One example is a smart streetlight; by adding connectivity, the light can report whether it’s overheating and therefore likely to fail soon. It can also report its position allowing maintenance crews to arrive quickly and affect a repair before pedestrians are plunged into darkness. The streetlight could also be used as a platform for other monitoring technology such as air quality or noise pollution. Looking the other way, utilities could, for example, send an instruction over the wireless link to temporarily brighten the illumination to aid first responders attending a road traffic accident.&nbsp;&nbsp;The beneficial impacts of wireless tech are a key reason for its booming popularity. For example, Bluetooth LE—a key connectivity technology for consumer, smart home, computer peripherals, and industrial automation among other applications—is set to reach 5.9 billion shipments in 2024, up from 4.9 billion in 2022[1].&nbsp;But there is one challenge that holds back even greater wireless adoption – RF engineering is notoriously tricky. That puts off inexperienced engineers.&nbsp;&nbsp;Because of Nordic Semiconductor’s efforts to abstract away much of the complexity by offering comprehensive software and hardware&nbsp;<a href="https://www.nordicsemi.com/Products/Wireless/Bluetooth-Low-Energy/Development-tools?lang=en#infotabs" target="_blank">design tools</a>, plus reference designs, implementing a wireless design has become easier - but it’s still not trivial. Modules can offer a simpler route to market. &nbsp;<h2>Wireless for the experienced&nbsp;</h2>If you have enough&nbsp;RF&nbsp;expertise, designing a fully-functioning,&nbsp;optimized, and certified wireless circuit is practical.&nbsp;Especially if you base the circuit on a highly integrated wireless SoC from Nordic’s nRF52 or nRF53 Series.&nbsp;That’s&nbsp;because&nbsp;the chips already include&nbsp;processor(s),&nbsp;memory,&nbsp;and&nbsp;many of the peripheral devices&nbsp;and I/O interfaces&nbsp;you’ll&nbsp;need&nbsp;for your end-product. These&nbsp;components&nbsp;are all embedded onto the&nbsp;Nordic&nbsp;chip&nbsp;and&nbsp;optimized&nbsp;to work seamlessly together.&nbsp;But there’s much more to an RF design than the SoC. The designer will also need to worry about the design and position of the antenna, impedance matching circuits, power regulation, component orientation, PCB trace length, crosstalk, electromagnetic interference (EMI), and plenty of other taxing design decisions. And things can get even tougher when developing a multiprotocol design that, for example, combines Bluetooth LE and Wi-Fi into a single product. Such a device will require more than one antenna with each needing its own impedance matching requirements.&nbsp;Once you’re done with the development, the next step is a lengthy and costly testing and certification process.&nbsp;&nbsp;If you get it right, there are some advantages to doing it from scratch. For example, you can closely match the wireless circuit performance to your application by trading off range or throughput for superior battery life. Or trading off antenna sensitivity against a more compact solution. It’s also possible to lower the Bill of Materials (BoM) and produce a more compact solution by designing from scratch.&nbsp;But if you get the design even slightly wrong, you might face multiple design iterations to achieve a satisfactory performance. That costs time and money - and prolongs the time-to-market.&nbsp;<h2>The benefits of a module&nbsp;</h2>For the developer with less RF engineering experience a module can make things much easier. The module maker has already completed the challenging parts of the RF design allowing you to drop-in the solution to your design - confident it will function well.&nbsp;&nbsp;When using a module, the development cycle for the wireless product will be drastically shortened – allowing the product to reach market quicker. Alternatively, because much less time will be needed on the RF subsystem design, the development team can allocate more hours to working on other product hardware and firmware features that will really differentiate the end-product from rivals.&nbsp;Module makers have lots of experience, so the performance of their devices is high. They are also experts at squeezing the best performance into the smallest space, keeping end-product form factors nice and compact. For example, to reduce the device footprint, module makers have access to specialist packaging technology that allows them to incorporate wafer level chip scale packages (WLCSP) alongside passive components to help accommodate the SoC, RF Front End, Power Management IC (PMIC), and chip antenna in the smallest area.&nbsp;Further, modules makers are quick to embrace the latest SoCs from Nordic so you can be assured of the best performing SoC for the job. For example, there are dozens of modules with the high-end nRF5340 and nRF52840 SoCs together with those for Nordic’s mid-range and entry-level SoCs. Module makers are also already working on designs using Nordic’s fifth generation solutions, the&nbsp;<a href="https://www.nordicsemi.com/Products/nRF54H20" target="_blank">nRF54H</a>&nbsp;and&nbsp;<a href="https://www.nordicsemi.com/Products/nRF54L15" target="_blank">nRF54L</a>&nbsp;Series SoCs. There are also several module options that combine Nordic Bluetooth LE SoCs with the&nbsp;<a href="https://www.nordicsemi.com/Products/nRF7002" target="_blank">nRF7002</a>&nbsp;Wi-Fi Companion IC for developers needing this multiprotocol alternative.&nbsp;<h2>Tested and pre-certified&nbsp;</h2>With a discrete RF design, considerable time and money could be needed for the weeks of testing and design iterations needed to get things compliant with RF regulations and Bluetooth SIG requirements. And even after a successful test, it can take more weeks for certification to come through, delaying sales.&nbsp;In contrast, modules are typically supplied tested and pre-certified to industry requirements. Providing the module is incorporated into the product design without modification, this compliance carries over to the end-product.&nbsp;&nbsp;<h2>Working with Nordic’s module partners&nbsp;</h2>Nordic has teamed up with dozens of&nbsp;<a href="https://www.nordicsemi.com/Resources/Nordic-Partners/Third-party-modules" target="_blank" rel="noreferrer noopener">module makers</a>&nbsp;through its&nbsp;<a href="https://www.nordicsemi.com/Resources/Nordic-Partners" target="_blank" rel="noreferrer noopener">Nordic Partner Program</a>.&nbsp;These companies are trusted design partners and have worked with Nordic for many years. They know our technology inside and out. That means if you source your module from a&nbsp;Nordic&nbsp;partner you are guaranteed to get the highest performing product using the latest hardware and firmware – you&nbsp;can’t&nbsp;buy&nbsp;better.&nbsp;Designing an RF subsystem from scratch is possible and does potentially bring some optimization, space, and cost advantages. But it’s a job for a highly experienced engineering team. If you’d rather accelerate your project schedule, eliminate RF testing and compliance, and focus on what really differentiates your product from the competition then a module is the way to go. Things are made even easier by purchasing a module from a Nordic partner because you are then assured of the best service, the latest technology, and the widest range of options.&nbsp;Better yet, when basing your design on a module from a Nordic partner, you are still guaranteed support from Nordic and will still be able to use the company’s development tools and Software Development Kit to build and test application software. Finally, if you base your design on a module but later want to migrate to a discrete RF design when volumes really ramp up, Nordic will assist in that design transition.<hr><h3 id="isPasted">References</h3>1.&nbsp;<a href="https://www.bluetooth.com/blog/now-available-new-bluetooth-forecasts-and-trends/" target="_blank" rel="noreferrer noopener">https://www.bluetooth.com/blog/now-available-new-bluetooth-forecasts-and-trends/</a>&nbsp;

Wireless connectivity makes dumb products intelligent. Smart devices can transmit information about their surroundings and conditions while receiving instructions and updates. That in turn enables functionality that’s impossible for products operating in isolation.  

Using a Bluetooth LE wireless module to accelerate time-to-market

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from the final chapter of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzExMTI0MjE4NTYyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>The next years of this decade are going to be extremely exciting for AI, particularly Edge AI. And with Wi-Fi Services like Relay2 revolutionizing the access point market, the future is going to be very promising indeed. The surging demand for AI applications that offer real-time, low-latency, and privacy-conscious capabilities will usher in a wave of Edge AI implementations. These deployments are poised to become increasingly precise and efficient, capitalizing on advancements in communication networks, such as Wi-Fi 6, coupled with innovations in artificial intelligence (such as data-efficient AI) and the Internet of Things (IoT).&nbsp;This transformative landscape underscores the pivotal role played by researchers, industry leaders, and open-source communities in steering the trajectory of Edge AI development. The evolution of efficient Edge AI applications relies on the progress of various technologies designed to support edge devices and enhance the computational efficiency of AI functions, including Wi-Fi services.<h3 dir="ltr">Increased Adoption &amp; Integration with Edge AI</h3>As the demand for real-time processing and low-latency applications continues to surge, the integration of Edge AI with Wi-Fi services will follow suit. The agility and scalability of Wi-Fi seamlessly complement the requirements of edge computing and AI. For instance, the latest generation of Wi-Fi, Wi-Fi 6, promises much faster data transfer speeds that can reach up to five times the speeds of Wi-Fi 5. This is complemented by reduced power usage, increased capacity, and enhanced performance, providing higher connection reliability in environments with multiple connected devices. This is where Relay2 sets a standard with its Wi-Fi services, pushing for innovation that leverages advancements like Wi-Fi 6. With a dynamic system that ensures flexibility and security, Relay2 offers virtual access control and simultaneous HD video sessions that can support up to 128 sessions. This is further supported by high performance and management of heavy traffic, capitalizing on an average throughput DL that exceeds 2 Gbps and handles 1,024 clients concurrently.This is bound to grow and enhance the adoption and integration with Edge AI in order to enrich the user experience. By implementing AI at the edge for efficient data processing and leveraging Relay2’s proactive real-time analysis and natural language adaptability, businesses and organizations can elevate their user experience beyond merely improving connection reliability. This synergy allows for efficient processing closer to data sources, reducing latency and enhancing overall system responsiveness.With Wi-Fi 7 being the next generation of Wi-Fi, we could see an even more seamless and immersive user experience and an advanced Edge AI performance, building on its new features such as multi-link operation (MLO), 320 MHz superwide channels, and a 4k quadrature amplitude modulation (QAM). This convergence of state-of-the-art communications and information technologies, such as cloud-native Wi-Fi services, edge computing, IoT, and AI, is driving a massive leap in management efficiency and social productivity. The hybrid edge-cloud architectures and applications are likely to surge in the very near future, ensuring not only high speed and efficiency but also the ability to run multi-modal generative AI and language models at the edge . In the second half of this decade, we will arguably witness an unprecedented increase in the adoption of Edge AI across numerous applications, rendering the technology mainstream.<h3 dir="ltr">Computer Vision &amp; the Impact of Edge AI and Wi-Fi</h3>One area where the convergence of Edge AI and Wi-Fi services is poised to have a high impact is computer vision applications. With the capability to process data locally, Wi-Fi-empowered edge devices can execute intricate computer vision tasks with unparalleled speed and efficiency. This transformative shift not only minimizes reliance on centralized cloud servers but also allows positioning systems to optimize energy and costs, enabling applications such as facial recognition, object detection, and automated surveillance to operate seamlessly in real time.With localization techniques such as Wi-Fi-based positioning systems (WPS) and the advent of convolutional neural networks (CNNs), we can detect and extract spatial patterns from visual data in a remarkable manner. This has the potential to transform industries, including healthcare, retail, automotive, and traffic management. Combining the high-processing capabilities of cloud computing with the real-time features of edge computing and the connectivity enhancements brought about by Wi-Fi technologies can enable AI to lift computer vision to a different level. Consider industrial automation in large factories and warehouses, smart cities with optimized traffic control, retail centers and shopping complexes with enhanced services and store layouts based on monitored customer behavior, and even remote medical services and patient monitoring that enable accurate diagnosis in real time. All these developments can take place by leveraging computer vision that is powered by AI at the edge.While there are still challenges standing before computer vision today, such as high processing power and high-quality data, the potential that Edge AI brings, supported by Wi-Fi capabilities that ensure fast and seamless data transfer - even in remote areas where accessibility would otherwise be difficult - will propel computer vision and enable it to be a much more potent and ubiquitous technology.&nbsp;With on-device inference capabilities and functionalities that enable computer vision within edge and mobile devices, image and pattern recognition can improve significantly, taking advantage of edge computing’s reduced latency, enhanced security, and minimized costs. Integrating AI into the mix enables even low-cost cameras to act as smart cameras, with deep learning methods enabling better identification and interpretation of data patterns. This is further enhanced by leveraging data from multiple devices connected via Wi-Fi, which provides AI with more comprehensive data, reinforcing its precision and understanding.<h2 dir="ltr">Conclusion: Wi-Fi-Powered Edge AI - A Technology for the Future</h2>Wi-Fi and Edge AI represent a technological paradigm shift with far-reaching implications. The convergence of Wi-Fi with Edge AI is not just a technological evolution but a fundamental reshaping of the digital landscape. As this symbiotic relationship matures, it propels us towards a future where Edge AI is not just a technology but an integral and indispensable part of our interconnected world. The potential for transformative applications is immense, urging both developers and sellers to explore the uncharted territories of innovation and contribute to the unfolding narrative of Edge AI's promising future.This not only addresses the computational needs of Edge AI but also aligns with the growing trend of connected devices in smart buildings, industrial settings, healthcare, retail, and smart cities. The integration of Edge AI with Wi-Fi services brings forth a boost in performance, user experience, and security measures, ensuring that sensitive data is processed locally. This transformation leads to the development of robust, always-on systems capable of meeting the stringent privacy requirements of contemporary applications and the ever-growing need for better performance, flexibility, scalability, and reliability.Throughout this report, we explored the capabilities and impact of Edge AI, especially when coupled with Wi-Fi services. We highlighted the valuable insights provided by Relay2, the leading Wi-Fi technology provider for the Edge AI market. Relay2's Service Points technology is designed to deliver exceptional application performance while enhancing security, privacy, and scalability at the edge.&nbsp;The Relay2 ServiceEdge Platform harnesses the power of Wi-Fi Services with Edge Computing to create a digital world where application performance and user experience not only remain uncompromised but are also enhanced. We also dove into particular applications and reviewed some use cases of Wi-Fi services edge computing. And finally, we took a look at the future of these technologies and how they will impact our businesses and way of living in the coming years. All this could not have been done without the support of Relay2 in developing this report.&nbsp;Relay2 is committed to empowering its partners by providing comprehensive, innovative solutions to ensure mutual success leveraging Wi-Fi Services with Edge Computing and the Relay2 ServiceEdge Platform. Therefore, developers and sellers are encouraged to partner with Relay2 to unlock the full potential of technology and shape a seamless digital future. The convergence of Wi-Fi with Edge computing can reshape the digital technology and business landscape, and Relay2 is at the forefront of this transformation.<h2 dir="ltr">Acknowledgments</h2>This report is the result of collaborative efforts between Wevolver and Relay2. Initial input was graciously provided by Relay2’s Eric Chen and Daniel Kwong, sharing their insights, expertise, and case studies, creating a robust technical substructure for the report. Then, the author further expanded upon this information to develop a comprehensive and insightful text, supported by the content and design team at Wevolver. Thank you to all contributors and supporters, and special thanks to Relay2.Download the full report with custom images, case studies and more, below.&nbsp;<iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 dir="ltr" id="isPasted">Read excerpts of the report chapters:</h3>Chapter 1: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-1-wi-fi-analytics-services-enabling-edge-ai" rel="noopener noreferrer" target="_blank">Wi-Fi Services Enabling Edge AI</a>Chapter 2: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-2-relay2-and-edge-ai" rel="noopener noreferrer" target="_blank">Relay2 and Edge AI</a>&nbsp;Chapter 3: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-3-applications-case-studies" rel="noopener noreferrer" target="_blank">Applications &amp; Case Studies</a>

The coming years will see a surge in Edge AI advancements, driven by real-time, efficient, and privacy-focused AI applications, alongside innovations in Wi-Fi and IoT, marking a promising future shaped by researchers, industry leaders, and open-source contributions.

AI at the Edge Report. Chapter 4: Future of Edge AI with Wi-Fi Technology

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from Chapter 3 of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwNTE0NjU1NDU5LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>The applicability of Wi-Fi Edge AI is fairly expansive and is growing by the day, spanning various industries and application areas. The most central aspects of this intersection of technologies are the real-time insights they provide, how these insights impact the speed and type of response, and how they are communicated across the network. Whether it is in smart healthcare, education, retail, or other application areas, Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time. Relay2 utilizes several Edge AI platforms to enhance the functionality of AI applications on the edge. In this chapter, we will take a look at some interesting use cases of Wi-Fi Edge AI, and we will see the impact of this technology convergence and the new opportunities it is opening in new and emergent technological spaces.<h2>Education / Smart Campus</h2>Wi-Fi Edge AI plays an important role in education-related applications, among which is remote learning integration, facilitating seamless and interactive remote education and bridging the gap between on-site and remote learning experiences. With localized content engagement pattern analysis and personalized experiences for students, Wi-Fi services and edge computing can help enhance and refine education content delivery.&nbsp;Campus facilities can also benefit significantly from integrating such technologies, especially in terms of security and surveillance, where Wi-Fi Edge AI can help analyze surveillance videos locally and in real time to recommend timely actions for security staff. It also powers use cases like attendance automation and traffic patterns, streamlining attendance tracking for educators and student flow analysis for operation enhancement.&nbsp;Another use case of Wi-Fi and edge computing can be seen in revenue generation, in which they enable intelligent, location-based advertising through audience behavior analysis for commercial partners. By leveraging these technologies, educational institutions can help promote campus services better, boost product marketing across campus premises and beyond, and enable efficient digital transactions.One example of applying Wi-Fi and edge computing in education is by WENet, an OEM partner of Relay2 in Vietnam. In order to support the University of Transport Technology in Vietnam in developing a digital technology infrastructure platform, WENet deployed Relay2’s Wi-Fi-enabled edge computing solution, making use of the advantages provided by Relay2 ServiceEdge Platform compared to conventional Wi-Fi networks. From stable bandwidth to fast processing speed, short deployment time, minimal service interruption time, and optimal operating costs, the features brought about by Relay2’s ServiceEdge Platform were highly effective. As a result, over 17 thousand students across three campuses were able to benefit from this platform, especially in terms of the following three key functions:<ul><li>Digital signage interacting with mobile devices to support two-way communication (university-to-student communication and student responses to university requests)</li><li>Students’ access to digital education materials from Relay2’s Service Points</li><li>Students’ ability to order food digitally from the cafeteria</li></ul>Such functions have not only enabled students to benefit from a Wi-Fi-powered edge computing platform but also helped collect analytic data for future AI processing at the edge. Read more about the WENet use case on the Relay2 website.<h2>Smart Healthcare</h2>Undoubtedly, one of the most important aspects of healthcare is real-time monitoring and real-time decision-making. However, as we have seen over the recent years with pandemic-caused crises, healthcare workers are more often than not overworked, and hospitals are resource-limited, which can limit their abilities to provide timely care. In order to ensure patient safety and health within hospital spaces and elsewhere, it is crucial to track, monitor, analyze, and act in real-time. All this can be made available by incorporating Edge AI and Wi-Fi. Whether it is remote monitoring and management, patient activity tracking, patient care, or even assistance during healthcare crises, hospitals, and medical personnel can benefit significantly from integrating Wi-Fi Edge AI into their processes.Smart healthcare comes in the form of connected healthcare, where AI-based smart devices, healthcare management software, and digital instruments are integrated into a “connected” healthcare system using a network protocol like Wi-Fi. As such, medical personnel would have access to all the medical-related information they need to provide the patients with the necessary medical treatment in the most effective and convenient way possible. This has been made possible by utilizing Edge AI and Wi-Fi technologies to empower the Internet of Medical Things (IoMT). In other words, healthcare personnel can leverage the low-latency capabilities of Edge AI processing and the ubiquity of Wi-Fi connectivity to access real-time data from diverse medical sensors, enabling timely decision-making and interventions and fostering a proactive approach to patient care.Consider intensive care units (ICUs), operating rooms, or other healthcare spaces, the use of Edge AI and Wi-Fi can augment the work of doctors, nurses, and clinicians by minimizing limitations, redundancies, and time allocated to activities away from direct patient care (such as documentation). As a result, medical workers can benefit from an emerging ambient intelligence , powered by edge computing, AI capabilities, and Wi-Fi. This can even be expanded to daily living spaces, which would support independent living, chronic disease management, mental health, and physical rehabilitation, particularly of elderly individuals.<h2>Smart Retail</h2>Global retail is almost always in flux, and both retailers and suppliers are grappling with the complexities of ever-changing consumer demand, behavior, and expectations. The continuous shifts in these dynamics create uncertainties in predicting future trends and exert significant stress on international supply chains and store operations. Navigating these challenges necessitates real-time adaptability to stay ahead in the retail industry.Edge AI emerges as a potent solution, offering retailers the capability to swiftly and precisely forecast daily demand while automating crucial aspects of supply chain logistics, customer engagement, and operational agility. This not only addresses challenges related to in-store supply management but also tackles issues in last-mile delivery costs, aligning with consumer expectations regarding timely deliveries.Within physical stores, retailers leverage Edge AI to combat issues such as shrinkage and stockouts, optimizing inventory management. Simultaneously, the application of Edge AI and Wi-Fi contributes to the creation of frictionless in-store experiences while prioritizing the health and safety of both employees and shoppers. The integration of AI in retail is thus transforming operations, offering a multifaceted approach to address the intricate challenges posed by the dynamic retail landscape.D.Phone, one of the largest cell phone retailers out of China, has deployed in-store Wi-Fi to enhance its customer experience and promote engagement as a way to offer a differentiated experience that would distinguish its &nbsp;D.Phone stores from competitors. They opted for Relay2’s wireless broadband solution, taking advantage of its unified native-cloud wireless networking and edge-service delivery.By leveraging Relay2 access points, D.Phone was able to offer high-quality customer experiences and deliver value-added services in-store. With its fast and reliable coverage in demanding environments like customer-dense spaces, including shopping centers and large venues, Relay2 access points enabled D.Phone to meet its customers' expectations and offer them the high-speed connectivity they desire. Moreover, with Relay2’s Edge services, D.Phone was able to run sales-generating applications and computation-intensive services locally and place content right at its &nbsp;D.Phone customers’ fingertips, thus reducing content download time to just seconds. This helped streamline the customer purchasing experience and circumvent bandwidth bottlenecks. It even enabled D.Phone to deliver new services to its customers, including app delivery and couponing. This has displayed an accelerated go-to-market process for D.Phone’s digital merchandise and a reinforced branding strategy. Read more about the D.Phone use case on Relay2’s website.<blockquote>“Relay2’s plug-and-play access points and cloud-based platform [have] given us a solution that lowers the cost of deployment and management.” - Wu Huan, CIO, D.Phone</blockquote><h2>Smart Buildings</h2>With the recent growth in smart homes and building automation systems, edge computing, AI, and Wi-Fi have become increasingly popular in this space. The integration of Edge AI with sustainable architecture and smart buildings has been rapidly gaining momentum and transforming the manner in which we construct and interact with our built spaces. With advantages like enhanced energy efficiency, optimized systems, personalized occupant comfort, and streamlined building maintenance, smart buildings are leveraging the real-time analysis capabilities of Edge AI and its integration with IoT and developing potential for more sustainable architecture and digital integration.Acting as a centralized intelligence hub, AI processes and interprets data obtained from an array of edge devices (IoT devices) such as sensors and actuators scattered throughout the building. This network of devices forms a comprehensive information system, providing valuable insights into various aspects of the building's operations. Through the implementation of AI algorithms, smart buildings gain the ability to efficiently monitor and regulate crucial functions like lighting, heating, ventilation, air conditioning, security, and energy consumption. Such an integration results in an environment that is not only responsive but also adaptive, catering to the dynamic needs and preferences of the building occupants.This can be further supported by Wi-Fi connectivity and cloud-based Wi-Fi services, in particular. Cloud-based Wi-Fi services enable centralized management and control of Wi-Fi networks. This centralized approach simplifies the deployment and maintenance of Wi-Fi connectivity across the building, ensuring a more streamlined and scalable infrastructure. Furthermore, the cloud facilitates the storage and analysis of the vast amounts of data generated by IoT devices in Smart Buildings. AI algorithms require substantial data inputs to make informed decisions, and cloud-based services offer the computational resources needed for processing and interpreting this data. It enables more sophisticated analytics, allowing for better insights into building operations, occupant behaviors, and energy consumption patterns.&nbsp;Similarly, the cloud's scalability can easily accommodate the dynamic nature of Smart Buildings, especially when the number of connected devices grows or changes. Just as importantly, cloud-based services enable remote monitoring, management, and updates of Wi-Fi networks and connected devices. This remote accessibility is invaluable for building administrators, allowing them to troubleshoot issues, implement updates, and optimize network performance without physically being on-site. In this regard, smart buildings can benefit meaningfully from Relay2’s innovative solutions. With advanced networking capabilities, Wi-Fi Edge Computing power, and intelligent analytics, users of Relay2’s ServiceEdge platform can ensure seamless connectivity and optimized operational efficiency.<h2>Smart Agriculture</h2>The Internet of Things (IoT) and edge computing have influenced the agricultural and farming industries quite extensively over the past decade, especially with the rapid rise of low-power wide-area networks (LPWAN) . Wireless communication protocols are, in fact, a vital part of smart agriculture systems, especially since the fields cover large areas that necessitate system components to be placed at remote locations. The integration of Wi-Fi and edge computing has been key to expanding the digital functionalities in agriculture, especially with the advent of AI at the edge, thus increasing the possibilities of smart agriculture over large areas.One type of smart agriculture that has been propelled by Edge AI and Wi-Fi services is precision farming. By deploying sensors and cameras in fields, farmers can gather real-time data on crucial factors such as weather patterns, soil conditions, crop growth, and pest infestations. This localized data processing enables farmers to modify and regulate their irrigation, fertilization, and pest control without delay, leading to an increase in crop yields and resource efficiency. The implementation of edge devices equipped with sensors extends beyond crop monitoring to include livestock health and behavior. Wearable devices on animals, such as cattle, provide early indications of illness or oestrus, empowering farmers to take timely actions, resulting in improved animal well-being, reduced rates of mortality, and higher farm productivity all around.&nbsp;Furthermore, the incorporation of Edge AI has paved the way for autonomous farming machinery, where tractors and drones equipped with edge devices can analyze field data in real time. This enables them to refine their routes, control planting depths, and identify and eliminate weeds in an autonomous manner. Not only does autonomous farming machinery reduce labor costs, but it also minimizes the use of chemicals, aligning agriculture with more eco-friendly practices. This is further empowered with the integration of Wi-Fi Services, allowing for centralized, remote monitoring and seamless connectivity between edge devices across large fields and in remote areas. The seamless integration of Edge AI and Wi-Fi technologies is proving transformative in making agriculture smarter, more efficient, and more sustainable over expansive agricultural landscapes.Relay2 offers smart farms state-of-the-art solutions that can help transform crop production, efficiency, and sustainability. These solutions seamlessly connect and monitor agricultural devices, collect real-time data, and leverage advanced analytics for informed decision-making. By optimizing resources, automating processes, and implementing precision farming, Relay2 empowers farmers to maximize yield and sustainability.<hr>This was an excerpt from Chapter 3 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwNTE0ODA2OTE3LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 dir="ltr" id="isPasted">Read excerpts of the other report chapters:</h3>Chapter 1: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-1-wi-fi-analytics-services-enabling-edge-ai" rel="noopener noreferrer" target="_blank">Wi-Fi Services Enabling Edge AI</a>Chapter 2: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-2-relay2-and-edge-ai" rel="noopener noreferrer" target="_blank">Relay2 and Edge AI</a>&nbsp;Chapter 4: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-4-future-of-edge-ai-with-wi-fi-technology" rel="noopener noreferrer" target="_blank">Future of Edge AI with Wi-Fi Technology</a>&nbsp;

Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time.

AI at the Edge Report. Chapter 3: Applications & Case Studies

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from Chapter 2 of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5NTQ4MTAzMTYyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;</iframe>The convergence of Wi-Fi and edge computing stands as a formidable force driving the ongoing shift to digital today. This convergence presents a pioneering paradigm for connectivity. It empowers enterprises with the capabilities of both managed Wi-Fi services and on-device data processing at the edge, enabling them to stay in step with, if not one step ahead of, the evolving digital landscape.&nbsp;Wi-Fi analytics services, in essence, revolutionize Wi-Fi deployment through a cloud-based service model, offering a complete package of managed Wi-Fi infrastructure and services. This strategic approach spares organizations from the significant capital investments typically associated with Wi-Fi infrastructure, affording them the opportunity to harness the expertise of service providers for broad network management. As a result, businesses can concentrate on their primary operations without having to worry about the intricacies of network maintenance. Simultaneously, the advent of edge computing ushers in a paradigm shift by migrating computational processes to the data source, thereby reducing latency and enabling real-time analytics and decision-making. This strategic switch from centralized computing models results in a notable enhancement of response time and operational efficiency, thanks to reduced bandwidth requirements and lower latency.At the heart of this technological transformation are the edge applications, which play a pivotal role within the Wi-Fi-edge-computing space. These applications harness the potential of edge computing for localized data processing and analytics, giving rise to real-time insights, seamless integration of artificial intelligence, advancements in IoT, and immersive user experiences. AI applications at the edge can accelerate innovation and enable organizations from various sectors to upgrade their services and maximize their operational efficiency.<ol id="isPasted"><li dir="ltr">Empowering Organizational Agility:&nbsp;The convergence of Wi-Fi and Edge Computing offers a dynamic solution that equips organizations with the ability to scale their Wi-Fi infrastructure in response to ever-evolving demands. By executing localized data processing and applications at the edge reinforced with Wi-Fi Analytics Services, businesses can seamlessly expand their network infrastructure and minimize their reliance on centralized data processing, thus optimizing bandwidth utilization and curtailing expenses.</li><li dir="ltr">Improving Cost-Efficiency and Streamlining Infrastructure Management:&nbsp;With Wi-Fi Networking and Edge Computing convergence, organizations can delegate the management and upkeep of Wi-Fi networks to service providers, hence alleviating the complexities of network infrastructure management while reaping the benefits of trustworthy and proficient Wi-Fi services. This also minimizes the initial financial burdens associated with building and maintaining Wi-Fi infrastructure. This integration yields the merits of both a cloud-managed Wi-Fi framework and local data processing, delivering immediate data insights and facilitating real-time decision-making.</li><li dir="ltr">Enhancing Performance and Reducing Latency:&nbsp;Leveraging local data processing at the network edge significantly mitigates latency in comparison to transmitting data across long distances to the cloud. This, in turn, results in prompt response times, enriched user experiences, and substantial improvements in application performance.</li></ol> In other words, Wi-Fi Services with Edge Computing emerges as a pivotal catalyst for digital transformation. Through its localized data processing capabilities, it delivers faster (low latency), more efficient (less bandwidth usage), and highly secure (enhanced security) data handling to enable real-time decision-making, which is a central factor of many applications, including autonomous driving, healthcare, and smart factories.<h3 dir="ltr">Relay2 ServiceEdge Platform: Reshaping Wi-Fi Access Point Technology</h3>In a recent study by Gartner, analysts estimated that by 2025, 75% of all enterprise-generated data will be created and processed outside of the cloud or traditional centralized data centers . These predictions highlight the significance of edge computing and its growth in enabling AI applications at the edge. This is where Relay2’s Service Point technology emerges, providing a state-of-the-art, all-in-one solution that combines Wi-Fi services with edge computing.Relay2's Service Point technology marks a substantial advancement in the field of Wi-Fi access point technology, pushing the boundaries of what conventional access points can achieve. Traditional access points may offer fundamental connectivity, yet they frequently fall short in providing the essential features required to fully exploit the potential of edge computing. The Relay2 Wi-Fi Service Point is a high-caliber Wi-Fi access point that incorporates inherent edge computing capabilities. It offers the capacity to host and execute local edge applications, which are either native software applications or equivalent counterparts of cloud-based applications. This convergence of edge computing at the Wi-Fi access point results in enhanced application and service performance, real-time interaction and response, and secure data processing, ensuring privacy and confidentiality.Using Relay2’s Service Point, businesses can leverage Wi-Fi services with edge computing to reap the following benefits:<ol><li dir="ltr">Efficient use of extra computing resources:&nbsp;By delegating computational duties from centralized servers to the Service Point devices, enterprises can enhance their network's overall performance and diminish latency. These devices have powerful processors and extensive memory, which enable streamlined handling of complex computing tasks at the edge of the network.</li><li dir="ltr">Enhanced performance, reliability, and security:&nbsp;Service Point devices have built-in security features and advanced encryption protocols that support organizations’ privacy and integrity of their data. Furthermore, these devices are engineered to manage substantial data workloads and sustain unwavering performance, even in challenging operational settings.</li><li dir="ltr">Streamlining infrastructure and achieving sustainable cost efficiency:&nbsp;Businesses can significantly benefit from an all-in-one device that integrates switches, routers, and computer servers, enabling them to optimize their network infrastructure and minimize long-term operational and maintenance costs. This comprehensive approach simplifies deployment and management processes, granting organizations the ability to allocate their resources with increased efficiency.</li></ol>Relay2 has taken one step further and has developed a cutting-edge platform called the ServiceEdge Platform. This platform is purpose-built to coordinate and oversee Relay2 Service Points and the edge-based applications they host, all orchestrated seamlessly from the cloud. The Relay2 ServiceEdge Platform comprises a network edge device (the Relay2 Wi-Fi Service Point), combined with a cloud portal service that allows for the management and coordination of Wi-Fi networking, Service Point, and edge computing. This platform enables the distribution, hosting, provisioning, and automation of custom-built or open-source edge applications via the Edge Apps Orchestrator. The overarching goal of the Relay2 ServiceEdge Platform is to offer a more efficient solution for WaaS providers to overcome the challenges of increasing operating costs and diminished ROI. By incorporating edge computing for advanced value-added services, this platform seeks to enhance the competitiveness of WaaS providers in the marketplace.Going beyond the conventional Wi-Fi access points focused on network connectivity, Relay2 Service Points introduce advanced edge-computing capabilities. These capabilities enable the hosting of edge applications within the Wi-Fi network in closest proximity to users and data sources. Relay2 expands the reach of edge computing, providing an opportunity for cloud computing applications to leverage the deployment of their edge-computing equivalents.&nbsp;The Relay2 Edge Apps Orchestrator stands out in the market due to a set of unique and compelling features. It introduces hierarchical, tiered-account cloud management services tailored to distributors, service providers, and end customers, facilitating Cloud Wi-Fi network management for Managed Service Providers (MSPs) while reducing operational expenses. Notably, the Edge Application Store within the Relay2 Wi-Fi Cloud Manager presents a distinct advantage, allowing MSPs to swiftly download and install prequalified applications for Service Points, expediting proof-of-concept for value-added services. Furthermore, Relay2 offers a cloud portal for provisioning, management, and automation of application hosting and settings on Service Points, enhancing user convenience through centralized configuration and administration. The platform also seamlessly orchestrates docker containers with its patented edge container system, streamlining the dynamic deployment of containerized edge applications while optimizing resource utilization and simplifying application management.Leveraging docker containers for the development of edge applications on Service Points, Relay2 fosters a developer-friendly, open-source environment, enabling IT technicians to create and deploy applications efficiently, thereby reducing time-to-market. Lastly, the Relay2 Cloud Manager provides feature-rich graphics, user interfaces, and monitoring capabilities, offering comprehensive insights into edge-computing applications and network performance for organizations.With Relay2 ServiceEdge Platform, businesses and developers can take part in the digital transformation and benefit from Relay2’s store of ready-made edge-computing applications to reduce their time to market and enhance their infrastructure’s scalability and flexibility with unparalleled automation and orchestration. They can also boost their operational efficiency with streamlined IT operations enabled by a centralized cloud-based management portal, all the while future-proofing their digital network infrastructure and unlocking new opportunities in emerging technologies like AI and IoT.This was an excerpt from Chapter 2 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5NTQ4MTU4OTc1LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 dir="ltr" id="isPasted">Read excerpts of the other report chapters:</h3>Chapter 1: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-1-wi-fi-analytics-services-enabling-edge-ai" target="_blank" rel="noopener noreferrer">Wi-Fi Services Enabling Edge AI</a>Chapter 3: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-3-applications-case-studies" target="_blank" rel="noopener noreferrer">Applications &amp; Case Studies</a>Chapter 4: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-4-future-of-edge-ai-with-wi-fi-technology" target="_blank" rel="noopener noreferrer">Future of Edge AI with Wi-Fi Technology</a>&nbsp;

Wi-Fi and Edge Computing: Transforming AI Applications


AI at the Edge Report. Chapter 2: Relay2 and Edge AI

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from Chapter 1 of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5MTI3Njg4OTg0LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe>Typically, artificial intelligence has been powered by cloud computing, given AI’s need for computing power and data-intensive processing. However, with the advent of edge computing, the AI landscape has been shifting, allowing for the rise of Edge AI. Edge AI is a revolutionary approach to how we deploy AI in various application areas, as it enables local computing and processing of data. That means the computing power is brought closer to the source of data, facilitating on-device data processing. With Edge AI, the system can make decisions in real time and with full contextual awareness by enabling AI features and capabilities directly on devices. Such a process would benefit from significant advantages brought about by Edge AI, including quick response, high bandwidth efficiency, and cost-effectiveness, to name a few.Unlike Cloud AI, which relies on remote servers for data processing and analysis, Edge AI is applied locally among a spectrum of devices spanning from data centers to IoT endpoints. The nature and location of the data being processed determine whether Cloud AI or Edge AI is more suitable for a particular application. For processing-intensive applications where latency can be compromised for the sake of in-depth data analysis and powerful computation, Cloud AI would be the ideal option. However, many applications are time-sensitive and require real-time data processing and prompt responses. This is where Edge AI takes center stage, minimizing the need to send data back and forth to a cloud server. This can take place at any location denoted as the edge, such as retail stores, hospitals, traffic lights, autonomous vehicles, and educational facilities.The following table explains the benefits and applicability of Edge AI and Cloud AI and how they differ from one another. Keep in mind that Edge AI and Cloud AI are not interchangeable technologies but rather applicable in different applications and scenarios. In fact, Edge AI and Cloud AI can even be complementary for systems that include both time-dependent and processing-intensive applications, which can benefit from a hybrid approach to data processing that integrates both technologies, as we’ll discuss later in this report.Table 1: Applicability and Benefits of Edge AI and Cloud AI<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NTg0MTM3NjM2LXRhYmxlIHJlbGF5LnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib"><h3 dir="ltr" id="isPasted">The Evolution and Adoption of Edge AI</h3>A 2023 report by Gartner on innovations in and around AI has highlighted the AI hype cycle for this year, showcasing the various advancements in AI and where they are today in terms of the public’s expectations . Among these innovations, we can see Cloud AI slowly navigating the so-called “Slope of Enlightenment” stage, where it is gradually transitioning toward mainstream adoption. In fact, Gartner expects Cloud AI to become mainstream in two to five years. Meanwhile, one of the fastest-growing innovations we can pinpoint on the cycle graph is Edge AI, showing a fast adoption rate to reach mainstream productivity in less than two years. This validates the potential that Edge AI has demonstrated in the past 2-3 years and shows that both edge and cloud computing can support AI applications in a symbiotic manner in the very near future.<a href="https://www.gartner.com/en/articles/what-s-new-in-artificial-intelligence-from-the-2023-gartner-hype-cycle" target="_blank" rel="noopener noreferrer"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NTg0MjE0MDU5LTAzXzExLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 768px;" class="fr-fic fr-dib">The hype cycle for AI in 2023 showed the rapid adoption rate of Edge AI. Credit: Gartner.</a>The recent developments in Edge AI have opened up new opportunities for devices to operate with human-like intelligence, regardless of their location. The successful deployment of AI models at the edge can be attributed to innovations that have significantly contributed to today’s digital transformation. For instance, neural networks and AI infrastructure have reached a level of maturity enough to pave the way for generalized machine learning. Organizations are now able to train AI models and deploy them in production at the edge. Besides, the recent advanced Edge AI accelerator chipset development, such as Axelera Metis, with high performance and low power budget, has made it possible to integrate these AI capabilities at a low power budget and with very high inference speed. Relay2 is pioneering this embedded integration with Wi-Fi Access Point, the edge of the Wi-Fi network. &nbsp;This is further strengthened by the widespread adoption of IoT devices, which is arguably the key reason behind the blowup of big data. Businesses can now collect every type of data from various sources. This availability of data and corresponding devices has made it possible to deploy AI models successfully at the edge.Given their remarkable ability to process and comprehend a range of unstructured data, including visuals, audio, temperature, language, faces, and more, AI algorithms have emerged as effective solutions for problems that end users face in real-time. Yet, deploying these AI applications primarily in centralized data centers like the cloud may prove impractical, especially with concerns about latency, bandwidth, and privacy. This is where the benefits of edge applications can facilitate AI deployment with their localized nature and decentralization, enabling real-time insights, high availability, and enhanced privacy.&nbsp;Nonetheless, Edge AI is not free of limitations, either. It still faces challenges, especially in data management, integration, security, miniaturization, and scalability. To overcome these challenges, a harmonious and purposeful co-design of hardware and software is necessary, and coordination with other technologies can prove quite fruitful. In fact, one of the most promising solutions for Edge Intelligence comes in the form of the convergence of Edge AI with cloud-based Wi-Fi Services, as we’ll see in the following section. Achieving miniaturization, model accuracy, energy efficiency, and cost-effectiveness simultaneously is a complex challenge. However, with proper coordination, optimization, and communication, we can facilitate the emergence of the next set of AI advancements at the edge.<h3 dir="ltr" id="isPasted">Next-Level Intelligence: Reinforcing Edge AI with Wi-Fi Services</h3>Since its inception about two and a half decades ago, Wi-Fi has shown significant development and adoption, with connection speeds skyrocketing from a few megabits to multi-gigabits per second. With this increase in speed, we have also seen an exponential rise in Wi-Fi-enabled devices, with almost every mobile device and computer now including Wi-Fi by default. In order to support the growing usage, demands, and throughputs of Wi-Fi, the network architecture has played a crucial role. Initially, Wi-Fi deployments were based on standalone access point architectures but later shifted to centralized hardware-based controller architectures. However, along with Wi-Fi functionalities like network optimization and mobility came some challenges, including scalability, reliability, manageability, and bottlenecks in performance, especially with increasing Wi-Fi traffic and link speeds. To tackle these challenges, service providers like Relay2 have been harnessing the power of the cloud and enabling vendors to shift from on-premise hardware controllers to cloud-native wireless controllers. Such a cloud-native system can provide the same benefits of centralized management without the constraints of physical hardware or associated adaptations. This not only enables greater flexibility but also offers more efficient and cost-effective management and coordinated control. As a result, this space has allowed for the rise of Wi-Fi-as-a-Service (WaaS), a subscription-based service that integrates software, infrastructure, and managed services to enable centralized management and coordinated control across different access points and automation of network monitoring and troubleshooting.Bringing Wi-Fi services and Edge AI into the same picture, we can see how their benefits align, where Wi-Fi enhances Edge AI’s scalability and integration capabilities, and Edge AI furthers the user experience of Wi-Fi solutions with data-driven insights and real-time analysis. For instance, looking at Edge AI’s integration challenges, we can still see cases of incompatibility stemming from differences in hardware, software, and communication protocols, which result from the unique architecture, specifications, and interface of every edge device. Employing Wi-Fi at this level enables secure, wide-coverage wireless communications, which further promotes interoperability and minimizes compatibility issues. Similarly, scalability challenges in terms of how Edge AI systems are handling increasing amounts of data and devices may compromise efficiency. The adaptability and scalability brought about by Wi-Fi services can help overcome these hurdles by enlarging a business’s network infrastructure and enabling effortless infrastructure management to meet the growing demand and shifting requirements.In other words, tying wireless and edge computing together can empower AI applications and reshape the business landscape to drive the digital transformation we are experiencing today. This convergence of Wi-Fi and edge computing presents a promising frontier for innovation, efficiency, and growth. As companies continue to recognize the value of this convergence, we can anticipate a marked increase in its adoption. As a result, edge computing would bring about a new wave of intelligent AI applications by integrating more computing power, which would allow adaptive learning and real-time responsiveness. This would be a significant step towards a more resilient system as the demand for always-on services continues to grow across various industries and application areas, including education, smart buildings, intelligent traffic management, smart agriculture, and smart retail. As more companies embrace the convergence of Wi-Fi and edge computing, we can expect to see a new era of technological innovation and efficiency.&nbsp;Right at the center of this technological fusion is Relay2, a leading Wi-Fi service provider that is on a mission to challenge the status quo of today’s Wi-Fi access point market. Relay2 is at the vanguard of the Wi-Fi edge-computing revolution, powered by their innovative ServiceEdge Platform, a Service Points technology that provides unparalleled performance, scalability, security, and privacy across a wide range of edge applications. In the next chapter, we will dive deeper into Relay2’s Wi-Fi services and explore how Relay2 is poised to reshape the Wi-Fi industry and how its patented platform is enabling more AI applications and capabilities within the edge-computing framework.This was an excerpt of Chapter 1 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. To read the full report, including in-depth case studies, download it below. &nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5MTI3ODU2MTAyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;</iframe><h3 dir="ltr"> </h3><h3 dir="ltr" id="isPasted">Read excerpts of the other report chapters:</h3>Chapter 2: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-2-relay2-and-edge-ai" target="_blank" rel="noopener noreferrer">Relay2 and Edge AI</a>&nbsp;Chapter 3: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-3-applications-case-studies" target="_blank" rel="noopener noreferrer">Applications &amp; Case Studies</a>Chapter 4: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-4-future-of-edge-ai-with-wi-fi-technology" target="_blank" rel="noopener noreferrer">Future of Edge AI with Wi-Fi Technology</a>&nbsp;

Intelligence at the Edge: Bringing AI Closer to You

AI at the Edge Report. Chapter 1: Wi-Fi Analytics Services Enabling Edge AI

Condition Monitoring, the backbone of smart industrial maintenance, is a proactive approach that leverages advanced technologies for real-time monitoring of machine conditions. This innovative strategy is pivotal in transitioning from time-based to condition-based maintenance in industrial environments.<h2>Condition Monitoring</h2>At its core, Condition Monitoring focuses on the real-time assessment of machinery by tracking key parameters such as temperature, vibration, pressure, and other vital indicators.&nbsp;This method stands out from traditional reactive or preventive maintenance strategies, which are either failure-induced or schedule-based. Condition Monitoring uses data analytics to identify patterns, trends, and anomalies in machine performance, thereby allowing for timely and precise maintenance interventions. This optimizes machine performance and significantly reduces the likelihood of unexpected breakdowns and associated downtime.<h3>Transitioning to Condition-Based Maintenance</h3>The shift from time-based to condition-based maintenance represents a significant advancement in industrial maintenance practices. Traditional time-based maintenance often leads to unnecessary downtime, as maintenance is performed at predetermined intervals, which may only sometimes be required.&nbsp;In contrast, Condition Monitoring enables maintenance to be scheduled based on the actual condition of the equipment. This data-driven approach leads to more efficient resource allocation, cost savings, and improved machine longevity. It's a smarter strategy emphasizing predictive maintenance, where actions are determined by the machine's condition rather than fixed schedules.<h3>Advantages of Condition Monitoring</h3><ul><li>Increased Equipment Reliability: Early detection of potential issues allows for proactive maintenance, minimizing unexpected failures and downtime.</li><li>Optimized Maintenance Planning: Maintenance activities are more data-driven, avoiding unnecessary interventions and focusing resources where needed most.</li><li>Cost Reduction: Early detection and intervention prevent minor issues from escalating into major failures, reducing overall maintenance costs.</li><li>Improved Safety: Continuous monitoring of critical machine parameters helps identify potential safety hazards, ensuring a safer working environment.</li><li>Enhanced Overall Equipment Efficiency: By maintaining machines in optimal condition, Condition Monitoring ensures efficient performance, reducing energy consumption and enhancing productivity.</li></ul><h3>The Process of Condition Monitoring</h3><h4>Monitoring Key Parameters</h4>Condition Monitoring depends on the continuous tracking of crucial machine parameters. These&nbsp;<iframe id="665da4b1ecaf80706bc13b0b" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/tdk-invensense-dk-42370-p-sensor-development-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> parameters vary across different types of machinery and industries. For instance, a manufacturing plant might focus on temperature and vibration, whereas a transportation system might monitor speed and fuel efficiency. Selecting these parameters requires a deep understanding of the machine's design, operating conditions, and potential failure modes.<h4>Data Collection and Analysis</h4>This process involves using advanced sensors and data collection systems that capture vital data points from machines. The collected data is then transmitted to a centralized system for processing and analysis. Sophisticated analytics are applied to the data to detect deviations from normal operation, enabling early intervention.<h2>Challenges in Condition Monitoring</h2>The below points outline the key challenges in implementing condition monitoring:Complex Data Collection and Integration<ul><li>Managing data from a diverse range of sensors and machines.</li><li>Standardizing data formats across different equipment and sensors.</li><li>Integrating data from multiple sources for comprehensive analysis.</li></ul>Scalability Issues<ul><li>Expanding the condition monitoring system to include more machines and sensors.</li><li>Ensuring the system can handle increasing data volumes without performance degradation.</li></ul>Infrastructure Limitations<ul><li>Establishing robust networking capabilities to support extensive data transmission.</li><li>Implementing sufficient data storage and processing capabilities.</li><li>Providing adequate computing resources for real-time data analysis.</li></ul>Maintenance and Operational Challenges<ul><li>Training personnel to effectively use and interpret condition monitoring data.</li><li>Implementing effective maintenance strategies based on condition monitoring insights.</li><li>Balancing predictive maintenance with traditional maintenance approaches.</li></ul>Cost Considerations<ul><li>Balancing the initial investment in condition monitoring technology against long-term benefits.</li><li>Managing ongoing costs associated with system upgrades and maintenance.</li></ul>Data Security and Privacy<ul><li>Ensuring the security of data collected from sensors and machines.</li><li>Addressing privacy concerns, especially in sensitive industrial environments.</li></ul>Data Analysis and Interpretation<ul><li>Developing sophisticated analytics to accurately interpret condition monitoring data.</li><li>Turning vast amounts of data into actionable insights for maintenance decision-making.</li></ul>These challenges highlight the need for a strategic approach in implementing condition monitoring systems to effectively leverage their benefits for predictive maintenance and operational efficiency.<h2>Moving Condition Monitoring Online</h2><h3>Transition from "Walk-around" to Online Maintenance</h3>The traditional "walk-around" method of condition-based maintenance, where technicians manually check equipment conditions, is evolving into a more efficient, online system. This change is particularly significant in industrial settings where manual inspections can be tedious and hazardous, especially for hard-to-reach devices.&nbsp;Online condition monitoring systems utilize permanent transducers connected to a multi-channel module for data acquisition, which then feeds into a PC-based processor station for data analysis and processing.&nbsp;This setup enables real-time monitoring and provides high-integrity data from otherwise inaccessible machine locations. The system is designed to automatically check sensor inputs against predefined alarm levels to determine the operating status of machines. Such systems are particularly valuable for machinery considered critical to operations, located in hard-to-access or unsafe areas, or in processes requiring frequent data assessment.<h3>Advantages and Applications of Online Systems</h3>Online systems offer numerous benefits over manual inspections. They reduce the time staff need to collect data, enhance the capacity for detailed machinery analysis, and provide frequent data sampling for faster diagnostics of problems. These systems are not only more efficient but also cost-effective, as they reduce the need for portable instruments and extensive labor.&nbsp;Online condition monitoring is ideal for processes that are event-driven or conditional, require immediate alarm notification, and where collaboration between operations and maintenance personnel is crucial.&nbsp;The integration of online monitoring with route-based tools allows for a comprehensive maintenance strategy, combining the strengths of both methods. For instance, online systems can immediately alert technicians when a machine parameter, like vibration in a gearbox, exceeds its threshold, while handheld devices provide flexibility in data collection and analysis.<h3>Implementing Online Condition Monitoring</h3>When implementing online condition monitoring, it is essential to understand which assets and failure modes should be monitored. Decisions should be based on the number of assets and types of measurements needed. The choice of a condition monitoring solution should consider factors like scalability, openness to new analysis techniques, interoperability with existing systems, and the overall cost-effectiveness of the solution.&nbsp;A successful online condition monitoring system involves data management, analytics, and the ability to detect reliably early indicators of potential issues. The system should balance minimizing false positives and negatives, providing actionable insights for predictive maintenance. This approach allows maintenance managers to schedule and plan maintenance only when necessary, leading to increased revenue, reduced costs, and enhanced safety.Transitioning to online condition monitoring in smart industrial environments offers significant advantages over traditional methods. It improves efficiency, safety, and reliability while reducing costs and downtime. The integration of such systems with existing maintenance strategies is key to achieving optimal asset performance and longevity.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4MzU2MzgxNzM0LWxvd3Jhb25lIDEucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib"><h2 id="isPasted">LoRaWAN in Condition Monitoring</h2><h3>Wired vs Wireless Condition Monitoring</h3>The transition from wired to wireless condition monitoring systems introduces a marked change&nbsp;<iframe id="65f3a84056faf563800a4811" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/nordic-semiconductor-nrf9161-multi-protocol-wireless-development-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> in setup complexity and cost. Wired sensor installations typically involve intricate cabling, which can be labor-intensive and expensive. In contrast, wireless systems offer a streamlined and cost-effective solution for deploying sensors across various locations, particularly in complex industrial settings.<h3>LoRaWAN in the Wireless Landscape</h3>LoRaWAN emerges as a formidable option in the wireless technology arena, especially when compared to other wireless protocols like Wi-Fi, Bluetooth/Bluetooth Low Energy (BLE), and LTE (Long-Term Evolution). Each of these technologies has its strengths and limitations, influenced by their inherent design to balance range, power consumption, and bandwidth.<ul><li>Wi-Fi: While Wi-Fi excels in high bandwidth, it is limited by shorter range (often not extending beyond 15 meters) and higher power consumption, making it less suitable for scattered IoT devices.</li><li>Bluetooth/BLE: Similar to Wi-Fi, Bluetooth and BLE are more focused on short-range communication. They are ideal for small-scale consumer IoT applications but may not be the best fit for industrial IoT due to their limited range.</li><li>LTE: Cellular technologies like LTE offer broader coverage and support for both low and high transmission bandwidths. However, they may involve higher power consumption compared to LPWAN (Low Power Wide Area Network) technologies like LoRaWAN.</li></ul>&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4MzU2NDIxNTAyLWxvd3Jhb25lIDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">LoRaWAN, with its long-range capability (several kilometers) and low power consumption, is uniquely positioned for condition monitoring applications. This technology is particularly efficient in sending small packets of data, such as those required for monitoring temperature, humidity, and other environmental variables. Devices on a LoRaWAN network can operate for years on a single battery charge, thanks to its low power design. Additionally, LoRaWAN's star network topology, where each device node communicates with a specific gateway, makes it a robust choice for IoT deployments in varied and challenging environments.&nbsp;<iframe id="65ba23f2cb56854ce719756b" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/advantech-wise-2410sk-na-starter-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>In the context of IoT, LoRaWAN's advantages are evident when considering the requirements of different use cases. For instance, its ability to efficiently handle small data packets over long distances makes it an excellent choice for applications like asset tracking, environmental monitoring, and smart agriculture.&nbsp;On the other hand, technologies like Wi-Fi and BLE might be more suitable for scenarios requiring higher data throughput over shorter distances, such as in smart homes or retail settings.<h2>Conclusion</h2>LoRaWAN Wireless Condition Monitoring represents a significant leap forward in industrial maintenance. By transitioning from time-based to condition-based maintenance, it offers a more efficient, cost-effective, and data-driven approach. This technology stands out in its ability to facilitate real-time tracking of key machine parameters like temperature, vibration, and pressure, thus enabling predictive maintenance.LoRaWAN, with its long-range, low power capabilities, is particularly suited for this task, overcoming the limitations of traditional wired systems and other wireless technologies like Wi-Fi, Bluetooth, and LTE.&nbsp;Despite facing challenges such as data integration, scalability, and infrastructure demands, the benefits—increased equipment reliability, optimized maintenance planning, cost reduction, improved safety, and enhanced overall efficiency—make it an invaluable tool in modern industrial environments.&nbsp;As industries increasingly adopt smart technologies, LoRaWAN Wireless Condition Monitoring emerges as a pivotal solution for advancing operational excellence and sustainability in the ever-evolving landscape of industrial maintenance.<h2>&nbsp;References</h2><ol start="1" type="1"><li><a href="https://sensemore.io/condition-monitoring-smarter-future-in-industrial-maintenance/" target="_blank">https://sensemore.io/condition-monitoring-smarter-future-in-industrial-maintenance/</a></li><li><a href="https://www.iotforall.com/condition-monitoring-via-lorawan" target="_blank">https://www.iotforall.com/condition-monitoring-via-lorawan</a></li><li><a href="https://www.mokolora.com/lora-and-wireless-technologies/" target="_blank">https://www.mokolora.com/lora-and-wireless-technologies/</a></li><li><a href="https://blog.pruftechnik.com/the-advantages-of-online-and-route-based-condition-monitoring-tools/" target="_blank">https://blog.pruftechnik.com/the-advantages-of-online-and-route-based-condition-monitoring-tools/</a></li><li><a href="https://www.plantservices.com/monitoring/condition-monitoring/article/11292115/addressing-challenges-of-online-condition-monitoring" target="_blank">https://www.plantservices.com/monitoring/condition-monitoring/article/11292115/addressing-challenges-of-online-condition-monitoring</a></li><li><a href="https://reliabilityweb.com/articles/entry/transitions" target="_blank">https://reliabilityweb.com/articles/entry/transitions</a></li><li><a href="https://www.flir.com/discover/professional-tools/what-is-condition-monitoring-guide/" target="_blank">https://www.flir.com/discover/professional-tools/what-is-condition-monitoring-guide/</a></li></ol>

Condition Monitoring with LoRaWAN: A guide to its effectiveness in industrial maintenance, the transition from traditional methods, and overcoming implementation challenges