As the world continues to embrace the Internet of Things (IoT), the demand for efficient power management solutions for IoT devices is on the rise. 

What Are the Best Applications for IoT in the New World of IC Power Management?

In today's competitive landscape, organizations can ill afford the risks of unplanned downtime and premature asset failure. This comprehensive guide unveils smart preventive maintenance strategies to minimize operational disruptions while maximizing productivity and ROI.

Preventive Maintenance: Optimizing Asset Performance and Longevity

<h2 id="isPasted">1. What is LoRaWAN?</h2>LoRaWAN is a standard within LPWA (Low Power Wide Area) wireless communication that uses the unlicensed band (sub-GHz band) that does not require a radio station license and features wide-area and long-distance communication as well as low speeds and low power consumption. LoRaWAN is a form of non-cellular LPWA that was established by the non-profit LoRa Alliance and recognized as an international standard by the International Telecommunication Union (ITU) in December 2021.LoRaWAN is a wireless network system that is used by connecting one or a small number of gateways with many end devices*1 equipped with a LoRaWAN module. LoRaWAN does not require a carrier communications network and it enables companies to build and operate their own networks, which makes it easy to introduce regardless of the application and business scale, and the number of users is increasing every year.*1 For example, communications devices that control device applications such as general lighting, cameras, and other sensors.<h3>1.1 Comparison of LoRaWAN (Non-cellular LPWA) and Cellular LPWA</h3>The LoRaWAN non-cellular LPWA standard is able to keep operating costs low compared to signing an agreement with a carrier and using their line. Furthermore, you do not need to consider the location where it will be used or whether stable communication with the carrier's base station is possible. In addition, because it enables you to build a complete network environment on your own, LoRaWAN can implement a private and secure wireless communications environment that is not mediated by the lines of an external operator.Reference: <a href="https://article.murata.com/en-global/article/what-is-lpwa-wireless-communication-1#section-55863" target="_blank">3.3 Cellular LPWA and Non-cellular LPWA Specifications Comparison｜What Is Low-Power Wide-Area (LPWA) Wireless Communication? - Basics</a><h3>1.2 Primary LoRaWAN Applications</h3>The primary applications of LoRaWAN include smart meters, smart cities, smart buildings, and enhancing the intelligence of public transportation in community infrastructure as well as support for IoT in the manufacturing industry, tracking of logistics cargo and people through location information, environmental sensing, smart agriculture, etc. Because it enables operation with a comparatively low cost that is not affected by the service area restrictions of carriers in contrast to cellular LPWA, LoRaWAN is attracting increased attention around the world as a means of wireless communication that is suitable for IoT and M2M in diverse fields.The following page introduces several examples utilizing LoRaWAN. <a href="https://article.murata.com/en-global/article/introduce-to-lorawan-2#section-59239" target="_blank">4. Examples of IoT Solutions Utilizing LoRaWAN｜LoRaWAN (Non-cellular LPWA) Primer – From Fundamentals to IoT Application Examples (2)</a><h2>2. LoRaWAN Communication Protocol Stack – Roles of LoRa and LoRaWAN –</h2>By looking at the communication protocol stack that is implemented, we can understand the features of those communication systems in many cases. (The communication protocol stack is explained in the&nbsp;<a href="https://article.murata.com/en-global/article/introduce-to-lorawan-1#section-59227" target="_blank">"Column – What Is the Communication Protocol Stack?"</a> section at the bottom of this page.) Figure 1 shows the LoRaWAN communication protocol stack. Here, we explain the LoRaWAN protocol stack as well as the respective meanings and roles of LoRa and LoRaWAN in the protocol.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEzNzY5NjU3MzkxLWxvcmF3YW4xLWltZzAwMDFfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 1 LoRaWAN communication protocol stack<h3 id="isPasted">2.1 What is LoRa (Physical Layer)?</h3>The "LoRa" shown in the Physical Layer at the bottom of Figure 1 is an abbreviation of "Long Range" and refers to the wireless modulation method developed by U.S. company SEMTECH based on CSS (Chirp Spread Spectrum), which is a type of spectrum spread technique. Furthermore, the LoRa ISM band*2 is established by country and region as shown in Table 1.<table><caption>Table 1 LoRa frequency band by region (partial)</caption><thead><tr><th>Region(country or territory)</th><th>Name</th><th>Frequency band(MHz)</th></tr></thead><tbody><tr><td>Europe</td><td>EU868/EU433</td><td>863-870/433-435</td></tr><tr><td>U.S.</td><td>US915</td><td>902-928</td></tr><tr><td>China</td><td>CN779/CN470</td><td>779-787/470-510</td></tr><tr><td>Japan</td><td>AS923</td><td>920-928</td></tr><tr><td>Australia</td><td>AU915</td><td>915-928</td></tr><tr><td>India</td><td>IN865</td><td>865-867</td></tr><tr><td>Indonesia</td><td>AS2</td><td>923-925</td></tr><tr><td>South Korea</td><td>KR920</td><td>920-923</td></tr><tr><td>Malaysia</td><td>AS1</td><td>920-923</td></tr><tr><td>New Zealand</td><td>AU915</td><td>915-928</td></tr><tr><td>Singapore</td><td>AS1</td><td>920-923</td></tr><tr><td>Taiwan</td><td>AS2</td><td>923-925</td></tr><tr><td>Thailand</td><td>AS2</td><td>923-925</td></tr></tbody></table>*2 The ISM band is a frequency band established by the International Telecommunication Union (ITU) that can be used without a license in the fields of industry, science, medicine, etc. The ISM band includes frequency bands that are universal and those that are region (country and territory) specific. The latter type of band is established for LoRa.<h3 id="isPasted">2.2 What is LoRaWAN (MAC Layer)?</h3>The MAC*3 Layer LoRaWAN is the name of the non-cellular LPWA standard while also referring to the LoRaWAN network communication protocol (rules of communication). Under LoRaWAN, each end device connects to the gateway via the MAC (Device ID) without an IP to communicate wirelessly.Moreover, the MAC options include Class A, Class B, and Class C, which differ in terms of the upstream and downstream communication schemes and intervals in the two‐way communication between each end device and the gateway as well as the switching behavior of the receiving slot on the device side related to power consumption, etc. The low power consumption Class A is often used when running a device with a battery for a long period of time with little reception standby time on the device side. At the same time, other classes can be separately used according to the objective and environment such as when communicating with low latency while continuously supplying power to the device, etc.*3 MAC is an abbreviation of "Media Access Control," and within the hierarchical communication protocols, it establishes methods for signal transmission timing control, the division of data to be transmitted, the assembly (transmission) and disassembly (reception) of frames with a destination address and other added control data, error detection, etc. in addition to the definition and allocation of the MAC address, which identifies devices.<h2>3. LoRaWAN Network Construction – Configuration of the LPWA Devices, Gateway, Servers, etc. –</h2>Because LoRaWAN is a non-cellular LPWA standard, it does not use carrier base stations and communications networks, as is the case in the wireless communications of cellular LPWA devices. Under LoRaWAN, data communication is carried out wirelessly between the LoRaWAN-compliant gateway and the end devices including sensors equipped with LoRaWAN modules, etc. Data is transmitted through this gateway to the network and application servers, etc., which run on communication protocols that differ from the LoRaWAN network. The example below introduces a primary network built using LoRaWAN.<h3>3.1 Example of Building Your Own LoRaWAN Network</h3>Because non-cellular LPWA does not require a radio station license, it enables companies to build a system on their own by preparing the LoRaWAN-compliant gateway, network servers, and application servers, etc. in addition to the end devices equipped with LoRaWAN modules.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEzNzY5NzA1NjA2LWxvcmF3YW4xLWltZzAwMDJfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 2 Example of building and operating your own LoRaWAN networkAs shown in Figure 2, the advantage of a LoRaWAN network is that it enables use of a private and secure wireless solution by building and operating the entire network oneself. Furthermore, while in some cases each server may be hosted on premises (internal environment), in other cases a cloud server contracted by the company may be used.<h3>3.2 Example of Building a LoRaWAN Network Using a Vendor</h3>In cases where it is not suitable to build a LoRaWAN environment on your own, such as usage for a specific period of time or if you lack the internal system integration or networking personnel, an alternative method is to use a vendor who sells or rents gateways that support the LoRaWAN communication protocol and offers cloud services, etc.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEzNzY5NzI2NzkyLWxvcmF3YW4xLWltZzAwMDNfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 3 Example of building a LoRaWAN network using vendor servicesAs shown in Figure 3, there are cases in which a company may sign a fee-based contract with a vendor for a LoRaWAN-compliant gateway and network servers or application servers according to the circumstances. The service details differ by vendor, but the ability to entrust the gateway implementation, server maintenance, etc. to the vendor is an advantage of such contracts. Furthermore, when it comes to LoRaWAN-compliant gateways that can connect and communicate with many devices, there are gateways that can only be used by the subscriber as well as plans that reduce usage fees by sharing a gateway between multiple subscribers.Moreover, cloud services are typically provided with the exception of the gateway. A monthly fee is required when subscribing to a gateway and servers. However, compared to cellular LPWA, which requires a mandatory contract with a carrier to use the cellular phone communication network, the service usage fees for network server vendors, etc. required to operate the LoRaWAN non-cellular LPWA standard are said to be low.<h2>Column – What Is the Communication Protocol Stack?</h2>Regardless of whether they are wireless or wired, telecommunications function by conforming to communication protocols (Reference:&nbsp;<a href="https://article.murata.com/en-global/article/basics-of-wireless-communication-2#section-58505" target="_blank">6. What Is a Communication Protocol?｜Basic Knowledge of Wireless Communication: Wireless Mechanism (2)</a>). Table 2 shows the role and correspondence of each layer of the communication protocol stack in the LoRaWAN model and the OSI Reference Model*4.<table><caption>Table 2 OSI Reference Model and the role of each layer, LoRaWAN model</caption><thead><tr><th colspan="2">OSI Reference Model</th><th>Roles and Examples</th><th>LoRaWAN model</th></tr></thead><tbody><tr><td colspan="2">Application Layer</td><td>Defines the functions that are required as an &nbsp; application such as sending and receiving files, &nbsp; etc. (HTTP, FTP, DNS, SMTP, POP, etc.)</td><td>Application</td></tr><tr><td colspan="2">Presentation Layer</td><td>Defines (SMTP, FTP, Telnet, etc.) &nbsp; the data expression format &nbsp; (encryption method, character code, etc.)</td><td rowspan="4">-</td></tr><tr><td colspan="2">Session Layer</td><td>Defines the steps related to the start and &nbsp; end (login and logout, etc.) of &nbsp; communication (TLS, NetBIOS, etc.)</td></tr><tr><td colspan="2">Transport Layer</td><td>Rules that ensure communication quality such &nbsp; as error detection and recovery in transmitted &nbsp; and received data (TCP, UDP, NetWare/IP etc.)</td></tr><tr><td colspan="2">Network Layer</td><td>Defines functions for relaying to different &nbsp; networks (IP, ARP, etc.)</td></tr><tr><td rowspan="2">Data Link Layer</td><td>MAC Layer</td><td rowspan="2">Defines the control procedures for &nbsp; transferring data (Ethernet, etc.)</td><td>LoRaWAN MAC&nbsp; (Class A / Class B / Class C)</td></tr><tr><td>LLC Layer</td><td>-</td></tr><tr><td colspan="2">Physical Layer</td><td>Defines connector shapes and other physical &nbsp; specifications (RS232C, etc.) for transferring &nbsp; data to communication channels as well as &nbsp; modulation systems in the case of wireless</td><td>LoRa modulation</td></tr></tbody></table>*4 The OSI Reference Model is an international standard model for a protocol stack. Currently, the protocol stack of this model is not directly used. However, because it is the fundamental reference model for the protocol stack, it is often compared to the various protocols that are implemented in devices.Table 2 shows that the LoRaWAN model stack has three layers while the TCP/IP model, which is the communication protocol of the Internet, has four layers, so we can see that the LoRaWAN model has a simpler protocol configuration. This means that it is easier to update the protocol and leads to improved response times.<hr id="isPasted"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713769894367-1713769894367.png" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don't hesitate to reach out. 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LoRaWAN is a standard within LPWA (Low Power Wide Area) wireless communication that uses the unlicensed band (sub-GHz band) that does not require a radio station license and features wide-area and long-distance communication as well as low speeds and low power consumption.

LoRaWAN (Non-cellular LPWA) Primer - From Fundamentals to IoT Application Examples (1)

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Consider the following details when conducting power profiling:<ol start="1" type="1"><li>Hardware and sensor configurations: Analyze the components and sensors used in the device and their power consumption characteristics.&nbsp;Understand how different hardware configurations impact energy usage.</li><li>Firmware settings: Examine the firmware settings and configurations to identify any potential areas where power consumption can be optimized. Adjust settings and parameters to achieve more efficient power usage.</li><li>Communication parameters: Evaluate the communication parameters used by the device, such as transmission frequency and data rate. Analyze how different communication settings affect power consumption and battery life.</li><li>Use cases and corner cases: Consider the different use cases and scenarios in which the device will be deployed. Investigate how the device's behavior and power consumption vary under different conditions. Pay special attention to corner cases that may have unique power consumption patterns.</li></ol>Continuous benchmarking is crucial throughout the product development process. Utilize UART clever printouts and correlate them with power consumption to identify specific components or features that may be draining energy. This analysis will provide valuable insights on areas that can be optimized for improved power efficiency. Remember to turn off UART once the analysis is complete to avoid any impact on the final product.Additionally, consider network variables that can impact power consumption. Import network log files to understand how factors like distance to the gateway or Node B, weather conditions, and device density within the network influence power consumption. These variables can significantly affect how the battery is drained and should be taken into account when estimating battery life.By iteratively calculating battery life based on power consumption profiles throughout the development project, developers gain valuable knowledge and intuition about the factors that affect the power profile. This understanding allows them to maintain the desired power profile despite changes in the development stack, ensuring optimal power usage and battery life.<h2>Refined battery selection with battery profiling</h2>Understanding the power consumption behavior of an IoT device goes beyond relying solely on data sheet information. It involves conducting a critical analysis to assess the battery's performance in the unique scenario relevant to your project. This process provides insights into the battery's efficiency, stability, and suitability for the deployment.<h2 id="isPasted">Defining a Battery Profile</h2>A battery profile is not just a general overview; it is a tailored description of how a battery discharges under specific loads in particular environments. You can find such profiles in the battery's data sheets. To select the ideal battery for your solution, you need to <a href="https://www.qoitech.com/battery-toolbox/" target="_blank">create profiles</a> that align with your device's power requirements. Additionally, it is beneficial to profile several battery alternatives from different brands, batches, and temperatures to gain a thorough understanding of their behavior.<img border="0" width="605" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351007606-1713351007606.jpeg" alt="En bild som visar skärmbild, Multimedieprogram, programvara, GrafikprogramvaraAutomatiskt genererad beskrivning" class="fr-fic fr-dii">By following these steps, you can gain a deeper understanding of the power consumption behavior of your IoT device and make informed decisions when selecting the most appropriate battery for your project.<h2>Accelerated Battery Profile</h2>To create a battery discharge profile that aligns with your device's current consumption profile, you may need several months or even years. Thus, it is essential to develop an accelerated discharge profile. Here are some best practices to create an accurate and helpful profile:Maintain High Discharge Consistency: Coin cell batteries are particularly sensitive to high discharge, so it is crucial to match your device's peak current. Lithium-ion rechargeable batteries can withstand higher discharge currents, while alkaline batteries fall in between.Shorten Cycle Time: Determine the low discharge time the battery requires to recover.Increase Sleep Current: Ensure the battery can recover even in high discharge. Consult with Manufacturers: Seek assistance from battery manufacturers to verify your assumptions for the batteries you want to profile.<h2>Accuracy Considerations</h2>It's worth noting that precisely matching the discharged energy in the accelerated profile to the original profile may not be feasible, which could affect the profile's accuracy. The less acceleration used, the more accurate the results, but this method's level of accuracy is usually adequate for IoT implementations. It ensures a comprehensive real-world understanding of the battery's performance, contributing to successful IoT solutions.<h2>Profiling Different Battery Chemistries</h2>Here is an example from a customer case with LoRaWAN waste management IoT device. For this specific application, we profiled two distinct electro-chemistries encompassing six brands, including multiple samples from each brand. The profiling was carried out at room temperature, using an accelerated battery profile developed with input from battery manufacturers. Comparing samples from multiple manufacturers allowed us to evaluate how different form factors and chemical compositions influenced the results. Profiling the batteries in various environments could be the next logical step to observe the available capacity deviation from these controlled profiles, given that the profiling occurred at room temperature.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351055997-otii-arc-battery-profiling.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiling set-up with Otii Arc ProBattery Profile AnalysisLM17500: Three samples of this battery were profiled, yielding an average capacity of approximately 3050 mAh before reaching the cut-off point, slightly higher than the data sheet capacity of 3000 mAh.CR123A: Two batteries were profiled, with an average capacity of about 1600 mAh, consistent with the data sheet for that specific temperature.Interestingly, alkaline batteries exhibited significant variations in available capacity based on the manufacturer, which is a crucial consideration if customers will be responsible for battery replacement.AAA: These batteries had capacities ranging from 1080 to 1150 mAh, with an average of around 1100 mAh. The data sheet indicated a capacity of 1200 mAh.AA: The AA batteries showed a wider range of capacities, from 2420 to 2730 mAh, with an average of approximately 2590 mAh. For example, the data sheet for Varta indicated a capacity of 2950 mAh.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351084975-battery.png" style="width: 100%px;" class="fr-fic fr-dib">Batteries profiled in this studyOur profiling process identified performance nuances across different battery brands, chemistries, and form factors. These insights are crucial for making informed decisions specific to the device and use case, going beyond the data sheet capacities. Conducting profiling in diverse environmental conditions, particularly temperature, could further enhance our understanding and contribute to a more resilient IoT device design. You want to see more details from this study? Download the <a href="https://www.qoitech.com/whitepaper/powering-iot-devices/" target="_blank" id="isPasted">white paper</a>.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351110704-picture6.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiles graphed for lithium manganese batteries from Saft and GP.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351132266-picture7.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiles graphed for alkaline batteries (AA and AAA) from five different brands.<h2 id="isPasted">Replaying the Battery Profiles</h2>Accurately measured battery profiles provide a more realistic and tailored understanding of the battery's capacity for a specific application, surpassing the information provided in mere data sheets when estimating battery life. By directly applying the profiled battery discharge to the device instead of using a standard power supply, you can determine the actual usable capacity and further enhance the accuracy of the estimation. The actual usable capacity depends on the behavior of the device itself, and in some cases, we have encountered as low as 20% of the measured capacity. Tools such as <a href="https://www.qoitech.com/otii-ace/" target="_blank">Otii Ace Pro</a> with <a href="https://www.qoitech.com/battery-toolbox/" target="_blank">Battery Toolbox</a> can replicate these battery profiles, effectively serving as profiled batteries for the IoT device. By adjusting the used capacity in the battery emulator of these instrumentsand monitoring when the device either shuts down or reboots, you can uncover the true, realistic usable capacity. This ensures a more precise understanding of the battery's potential in the context of the specific application.<img border="0" width="605" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351148170-1713351148170.png" alt="Battery emulation with OtiiBattery Toolbox. MEasured and saved battery profile can be replayed to mimic the actual usable capacity and battery behaviour." class="fr-fic fr-dii">Battery emulation with Otii Battery Toolbox<h2>Conclusion</h2>We propose a technique for selecting the ideal battery: initial selection based on a defined use case and data sheet, power profiling of the IoT device and the battery for the use case, and a refined battery selection using device power behavior to assess the battery's real-world performance for the specific use case and device. This nuanced approach enables developers to make well-informed decisions that boost battery life.

Once the first prototype of your IoT device becomes available, it is essential to start power profiling and estimating battery life. This process involves gaining a comprehensive understanding of the device's configuration and power consumption characteristics within its specific deployment context.

How to pick the right battery for an IoT device: A waste management case study

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While embedded systems tend to lack the processing horsepower of servers or even modern personal computers, the sheer number of devices is making them an increasingly valuable target for bad actors looking to run illegal botnets and cryptocurrency mining operations. One of the first major security-related wake-up calls for embedded system designers was the 2016 Nest thermostat botnet attacks. Given the consumer-facing nature of the particular Internet of Things (IoT) coupled with an increased sensitivity regarding privacy and security; the Nest botnet caused a huge amount of discussion. Those discussions tended to center on how companies should build security into their low-cost IoT products and how consumers can safely operate the devices in their homes and businesses.With the growing threat of cyberattacks, it is essential that developers keep security considerations in mind throughout the design process. By following some practical tips and recommendations, developers can guard against a wide range of attack scenarios. Read on for an outline of security measures developers can use in their embedded designs.<h2>Build Secure</h2>While there are numerous chip architectures, operating systems, and communications protocols; many IoT devices tend to be built around Arm®-based architectures, and if they run an OS it tends to be a Linux distribution. This commonality is good in many ways; lower costs and faster development times; it also comes with quite a few negatives. Attack vectors tend to become “one-size-fit-all”, especially for devices running a Linux-based OS. To mitigate the threats associated with widespread devices that share a common architecture, developers should implement the following “quick win” security design principles:<ul><li>Do NOT hardcode passwords into the firmware. Also, do not use a common default password for all devices. Require the user to create a custom username and password during device initialization.</li><li>Do NOT enable insecure protocols such as HTTP, FTP, or Telnet by default. Data going off the device via wired or wireless protocols must be strongly encrypted. Avoid “homebrewed” encryption solutions.</li><li>Ship the device with the most restrictive configuration possible and let the end-user make a proactive decision to reduce security-related settings.</li><li>All mechanisms used to access the devices should require authentication and authorization controls. Two-factor authentication (2FA) should be used if practical.</li><li>All user-facing inputs should be filtered to avoid injection-type attacks.</li><li>Implement a secure device management interface for the end-user that will allow them to manage their assets, update devices, monitor devices, and securely decommission the devices that have reached their end-of-life (EOL).</li><li>Over-The-Air (OTA) update mechanisms must be validated on-device. The update files must be sent encrypted en route to the device. Lastly, ensure there are anti-rollback features to prevent a device from being reverted to a previous, insecure firmware.</li><li>If third-party software libraries are used in the design of your device, they must be continually monitored to ensure that third-party updates are integrated and that they do not become deprecated. Abandoned software projects can become nasty vulnerabilities for your device. Change the third-party software default passwords before committing them to your project.</li><li>Limit what sensitive data should be stored on the device. Store such information in a secure enclave only.</li><li>Remember that with the IoT that embedded systems are only one part of a larger ecosystem. Ensure that security is built into the cloud, desktop, and mobile applications as well. Ecosystem security is only as strong as the weakest link.</li><li>Consider establishing a bug bounty program to encourage end-users and security researchers to submit flaws in a secure, responsible manner.</li></ul>Physical access to a device tends to be the game-over situation for devices. That doesn’t mean that there aren’t things that can be done to make it harder physically exploit these types of devices. Entire books have been written on making circuit boards and associated enclosures tamper-resistant but for a few “quick wins” consider the following physical design rules-of-thumb to harden your device:<ul><li>Pins for debugging ports such as JTAG and UARTs are very useful when developing and testing a device. They are also tempting targets for those seeking to reverse engineer a device with ill-intent. Obfuscating these pins and/or removing header pins for production units is recommended. Note that this will come at the expense of making it more difficult to troubleshoot once fielded. Designers must consider a balance between security and maintainability.</li><li>The use of adhesives, ultrasonic welding, and/or specialty security screws can make it more difficult to open a device.</li><li>Applying a non-conductive epoxy over sensitive components can obfuscate their identity and purpose.</li><li>You might be tempted to use older components that might have vulnerabilities. Be aware of the counterfeit components as well. If a deal seems too good to be true, it probably is. Balancing security and time-to-market considerations is not a decision to be taken lightly.</li><li>Multilayer boards can be used to route traces in a way that makes it harder to discern how the board functions.</li></ul>Some of the following recommendations might be a bit much for consumer-grade IoT devices. However, as we will elaborate on later, industrial control systems and defense systems would likely benefit from these more robust physical security measures:<ul><li>Build security features into the board itself, such as microswitches, mercury switches, or magnetic switches that can detect if a board is being unintentionally handled or opened. Nichrome wire or fiber optics can also be used. If the wire or fiber is negatively impacted by someone trying to tamper with a device, then there will be a detectable change in the current flow of the wire or the behavior of photons through the fiber.</li><li>Side Channel or glitching attacks, while perhaps not common, provide a unique advantage to adversaries in that they use the laws of physics against a device and thus are very difficult to prevent though can be detected. By attacking the timing or restricting the flow of electrons to a CPU, it’s possible to get a device to act in unintended ways that negate security features. Voltage and current sensors can be implemented onboard circuit boards to detect if glitching may be occurring, though there is potential for false positives.</li><li>Significant adversaries can employ x-ray machinery to peer into microchips and discover the topography of the transistors to determine function and more. Sensors that detect x-rays can be added to detect tampering, though can do nothing to prevent an adversary from extracting useful information.</li></ul>It should be noted that there is quite a dichotomy between the paradigms of security and openness. Security values obfuscation. Open hardware values understanding. Regardless, keep in mind the old adage that locks only keep honest people honest, and so too with security-at-large. For more information on how to build secure IoT devices, visit the Open Web Application Security Project (OWASP) IoT Project.<h2>Operate Secure</h2>Even if a manufacturer could implement all the best secure design principles in their product, they would be mostly for naught if the end-user does not operate their device in a secure manner.<ul><li>Change the default router name, router password, network name (SSID), and network encryption key. Be sure to use strong password principles and do not use the same password for both networks.</li><li>Segment your home network into two “virtual” networks so that IoT devices cannot be “seen” by the desktop computers, Network Attached Storage (NAS) devices, etc. To do this quickly and easily, use the guest network feature for your IoT network.</li><li>Most IoT devices rely on a smartphone app to control the device. Keep the app up to date and use 2FA for login if available.</li><li>Disable any features of your IoT devices that you do not intend to use.</li><li>Update the firmware of both your router and IoT devices on a regular basis.</li><li>When an IoT device reaches the end of life and no longer receives updates consider replacing it with a newer model.</li></ul><h2>Industrial Strength Security</h2>Consumer-facing IoT products may be plentiful, but their industrial counterparts, collectively referred to as Industrial Control Systems (ICS) manage numerous extremely important and potentially dangerous processes. Everything from energy production to factories uses embedded digital technology (referred to as Operational Technology or OT; in contrast to office-centric Information Technology or IT) to control the facilities and associated machinery responsible for performing the various processes. The ICS environment is sufficiently different from a strict IT environment that special considerations for hardening OT devices and ICS networks are warranted. The most fundamental principle is that ICS should not have a connection to the internet. While this seems like a no-brainer, it is surprising how often this fundamental rule is violated. For more information on how to secure ICS networks and devices, there are two security frameworks you should review: MITRE ATT&amp;CK for ICS and the MITRE ATT&amp;CK for Enterprise.The nature of where ICS systems are typically found (e.g., areas that are environmentally, chemically, or otherwise hazardous) means ICS has been designed to prioritize the availability of the systems over confidentiality. From a positive perspective, this typically means there are redundant systems, and those systems are designed to fail safely. However, ICS systems can be left in operations for several decades and may not always be kept up-to-date. In addition, many of the protocols are older and were built with efficiency, not security in mind. Bottom line, security in the ICS or IIoT space is uniquely challenging and best practices may be difficult to implement. However, embedded developers for such machinery should be cognizant of the need to modernize their design practices and incorporate security into future designs and not treat it as a bolt-on afterthought.

(Source: Nikolay N. Antonov - stock.adobe.com)

With the growing threat of cyberattacks, it is essential that developers keep security considerations in mind throughout the design process. By following some practical tips and recommendations, developers can guard against a wide range of attack scenarios.

Practical Tips for Embedded System Security

For thousands of years, humans have been building houses, roads, bridges, and markets that allowed us to live safer and more productive lives. But the tools of the trade have lacked the capability to let us do so as effectively as possible. &nbsp;Now, belatedly but perhaps inevitably, smart connectivity is helping to lay the foundations for improved productivity and worker safety in the all-important architecture, engineering, and construction (AEC) industry. To that end, technology companies are introducing a wide range of innovative products to power connected construction. &nbsp;<h2>The&nbsp;critical role of the&nbsp;building&nbsp;sector&nbsp;</h2>From humble beginnings, construction has culminated in giant cities where 55 percent of the world’s population resides, a figure, according to the UN, that’s set to rise to 68 percent by 2050.&nbsp; Today, the AEC sector is the largest in the global economy, responsible for employing around seven percent of the world’s working population, and about 13 percent of world’s GDP ($10 trillion) according to analyst McKinsey. And because around 50 percent of a construction project’s total cost relates to labor, &nbsp;skilled workers are the key to a project’s success.&nbsp;<h2>Tech&nbsp;provides a&nbsp;solution&nbsp;to productivity challenges&nbsp;</h2>Yet despite its importance, the construction industry has earned a reputation for being slow to innovate. As a result, the sector has often suffered from severe productivity challenges.&nbsp;Technology offers a solution for raising the game. The signs are promising; digital adoption is accelerating on the back of strong demand for more infrastructure, a shortage of skilled labor, and increased expectations for data transparency and integration. An estimated $50 billion was invested in AEC tech between 2020 and 2022—85 percent higher than the previous three years—according to the latest McKinsey research.&nbsp;Growth is being driven by increased uptake of the IoT, big data analytics, and AI, as well as a greater emphasis on sustainability. That’s allowing companies to take advantage of real time field reporting by connecting and tracking materials, equipment, and workers at the construction site.&nbsp;<h2>Enhanced productivity&nbsp;boosts the bottom line&nbsp;</h2>A construction project manager can now access a management platform with real-time project data and task alerts. This information enables fast decisions and speeds up workflows from the back office to the field, and onwards to the extended project team. And it removes the project silos that limit collaboration. These practices will also lead to improved margins.&nbsp;&nbsp;Connected construction offers several other advantages over manual operations. For one, it can improve communication and transparency on the worksite; for example, consider a worker reporting back to a supervisor via a smart device, or sensors and tags embedded in equipment providing key updates such as the location and status of a concrete mixer. Or connected vehicles like dump trucks, backhoe loaders, excavators, and mobile cranes, could enable location detection and monitoring of usage via embedded cellular and GNSS technology.&nbsp;&nbsp;<h2>Monitoring essential construction materials&nbsp;</h2>A critical requirement for the construction industry is monitoring essential construction materials like concrete for quality control. This requirement led German company ConcR to develop a&nbsp;<a href="https://www.nordicsemi.com/Nordic-news/2023/11/The-ConcR-Box-employs-Nordic-Semiconductors-nRF9160-SiP" target="_blank">material monitoring solution</a>&nbsp;that analyzes the characteristics of concrete as it cures, to check when it’s safe to proceed with the next stage of construction. The ConcR Sensors are attached to a rebar (a reinforcing steel bar used to strengthen concrete slabs) before the concrete is poured. The sensors provide key insights into the strength and durability of the cement or concrete by monitoring temperature, relative humidity, residual moisture, pH, and chloride levels.&nbsp;&nbsp;The Nordic&nbsp;<a href="https://www.nordicsemi.com/Products/nRF9160" target="_blank">nRF9160 SiP</a>-powered&nbsp;<a href="https://www.nordicsemi.com/Products/Wireless/Low-power-cellular-IoT" target="_blank">cellular IoT</a>&nbsp;solution provides data across the lifecycle of concrete and screed—a levelled layer of material applied to a floor or other surface—starting from construction until 25 years in operation. With this information, planners, engineers, contractors, and owner-operators gain data-informed insights about the condition of construction materials throughout their life.&nbsp;<h2>Putting worker safety&nbsp;first and foremost&nbsp;</h2>Beyond productivity gains, technology is essential to the safety of skilled construction workers on hazardous worksites.&nbsp;&nbsp;For example, by using sensors integrated into existing personal safety equipment such as hard hats, WakeCap Technologies’ solution connect workers across entire job sites.&nbsp;<a href="https://www.nordicsemi.com/Nordic-news/2021/01/Wirepas-Mesh-hard-hat-sensor-locates-wearer-across-large-sites-and-reports-activity-incidents" target="_blank">WakeCap</a>&nbsp;is a wearable product designed to overcome the challenge of “digitizing the construction sector’s field logistics and workforce”, according to the company. In operation, the hard hat-worn sensors track the wearer’s location and record knocks to the hard hat. In addition, WakeCap’s analytics compare the on-site work crew timing with staffing and project management plans, highlighting any unexpected problems early - helping avoid delays and extra costs.&nbsp;Thanks to wireless tech, construction equipment, vehicles, devices, personnel, and locations will communicate and work together using emerging connectivity platforms. Connected construction is here and the world is better for it.&nbsp;

Smart connectivity is helping to lay the foundations for improved productivity and worker safety in the all-important architecture, engineering, and construction (AEC) industry. To that end, technology companies are introducing a wide range of innovative products to power connected construction.  

Construction sector building on wireless tech foundation

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"></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"></iframe>

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

In today's fast-paced world, the demand for efficient, automated data input and verification systems is more pressing than ever across various sectors. From retail and logistics to healthcare and manufacturing, the ability to quickly and accurately process information can significantly enhance operational efficiency, reduce errors, and improve customer satisfaction. This growing need has spurred innovation in data capture technologies, highlighting the importance of reliability, speed, and adaptability in diverse environments.Enter the <a href="https://www.okdo.com/p/useful-sensors-tiny-code-reader/" target="_blank">Tiny Code Reader by Useful Sensors</a>, a cutting-edge solution at the intersection of convenience and technology. This device epitomises the advancements in artificial intelligence (AI), offering an innovative approach to reading QR codes and other data matrices. With its AI-powered capabilities, the Tiny Code Reader is designed to streamline the data capture and verification process, providing a seamless, effortless experience. Whether tracking inventory in a warehouse, authenticating tickets at an event, or facilitating contactless payments, this compact yet powerful tool can handle a wide range of applications with unprecedented ease and accuracy.What sets the Useful Sensors Tiny Code Reader apart is its size and its sophisticated integration of AI algorithms. These algorithms enable the device to quickly identify and interpret QR codes, even under less-than-ideal conditions, such as poor lighting or awkward angles. This level of efficiency and adaptability ensures that businesses and organisations can maintain high productivity levels and offer enhanced customer services, reinforcing the critical role of smart, AI-driven tools in the digital age.As we delve deeper into the capabilities and potential applications of the Tiny Code Reader, it's clear that this innovation is more than just a tool for reading codes—it's a gateway to a more efficient, connected, and technologically advanced future.<h2>The Power of AI in Simplifying Data Input</h2><h3 dir="ltr">AI You Can Trust</h3>The AI technology behind the Tiny Code Reader is designed for reliability and accuracy, allowing users to read QR codes swiftly and precisely. Such technology promises private and secure AI applications encapsulated in solutions like AI in a Box, highlighting Useful Sensors' commitment to delivering non-intrusive, efficient AI tools. These efforts align with the broader industry trends of making AI more accessible and trustworthy for various applications, ensuring the data input process through QR code reading is fast and error-free.<h3 dir="ltr">Built-in Camera and AI Integration</h3>The Tiny Code Reader ingeniously merges camera capabilities with AI technologies, eliminating the necessity for additional cameras or complex setup procedures. This integration is part of a trend where companies like Useful Sensors aim to embed AI tools into small, self-contained modules, focusing on privacy and offline functionality. By combining AI with camera technology directly on the device, the Tiny Code Reader can effortlessly interpret QR codes, streamlining the data input process without compromising on user privacy or requiring external hardware support.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711117235373-Useful-Sensors-Tiny-Code-Reader-OKdo-5.jpg" style="width: 100%px;" class="fr-fic fr-dib">The code reader is compact and packed with features. Credit: OKdo<h3 dir="ltr">Versatile Applications Across Industries</h3>With its capacity to streamline operations across various sectors, the AI-powered Tiny Code Reader demonstrates a wide array of applications in enhancing efficiency and productivity, particularly in equipment setup, stock control in logistics and retail, and manufacturing processes.In manufacturing, AI technologies like the one powering the Tiny Code Reader play a crucial role in automating and optimising production processes. For instance, AI can automate complex tasks, significantly reducing labour costs and improving productivity. This includes running continuous tracking and monitoring operations, spotting anomalies quickly, and building a central repository for operational data to ease employee transitions.AI enhances precision and efficiency for equipment setup, particularly through predictive maintenance and operational optimisation. It can process vast amounts of sensor data to detect inefficiencies and predict equipment maintenance needs before breakdowns occur, thus ensuring continuous and efficient production.AI-powered systems offer advanced inventory tracking and management capabilities in logistics and retail. These systems can predict optimal delivery routes and assess various scenarios for last-mile deliveries, thereby improving supply chain efficiency. AI's predictive capabilities also allow for real-time and predictive supplier assessment and monitoring, ensuring rapid response to supply chain disruptions.Across industries, the integration of AI in devices like the Tiny Code Reader underscores a significant shift towards smarter, more efficient operations. AI-powered technologies significantly increase operational efficiency, safety, and productivity by automating routine tasks, optimising production processes, and enhancing supply chain management.<h2>Key Features and Advantages</h2><h3 dir="ltr">Easy to Embed in Products</h3><ul><li dir="ltr">The Tiny Code Reader boasts a compact, streamlined design, allowing seamless integration into various products and systems, from handheld devices to industrial machinery. It enhances their capabilities without compromising space or design aesthetics.</li><li dir="ltr">Its small footprint and low power consumption make it an ideal choice for adding QR code reading functionality to battery-operated and portable devices, ensuring they remain lightweight and efficient.</li></ul><h3 dir="ltr">Affordable Price Point</h3><ul><li dir="ltr">Priced competitively, the Tiny Code Reader democratises access to advanced QR code scanning technology, making it a viable option for startups and established companies across various retail, logistics, and healthcare sectors.</li><li dir="ltr">This affordability helps to lower the entry barrier for implementing cutting-edge technology in traditional and innovative applications, enabling businesses of all sizes to enhance their operations and offer new services.</li></ul><h3 dir="ltr">Fast Development Cycle</h3><ul><li dir="ltr">Designed with rapid integration, the Tiny Code Reader supports a fast development cycle, featuring easy-to-use SDKs and APIs that streamline the process of embedding the device into projects, reducing time to market.</li><li dir="ltr">Compatibility with common development environments and languages facilitates effortless incorporation into existing systems, allowing developers to focus on innovation rather than integration complexities.</li></ul><h3 dir="ltr">I2C Connectivity</h3><ul><li dir="ltr">The inclusion of I2C connectivity underscores the device's flexibility and compatibility with a broad range of single-board computers (SBCs) and microcontrollers, from hobbyist projects to professional-grade embedded systems.</li><li dir="ltr">The I2C interface ensures simple and efficient communication between the Tiny Code Reader and other devices, enabling developers to build sophisticated, multi-functional systems that include features such as data logging, user interaction, and wireless communication alongside QR code reading.</li></ul> These features collectively position the Tiny Code Reader by Useful Sensors as a versatile, cost-effective, and user-friendly solution for integrating QR code scanning capabilities into many products and applications, fostering innovation and efficiency across industries.<h2 dir="ltr">Benefits of Implementing the Tiny Code Reader</h2>Implementing the AI-powered Tiny Code Reader by Useful Sensors brings significant benefits across various sectors, notably enhancing operational efficiency, reducing errors, and improving overall quality assurance in processes. Here's a closer look at how this innovative device can transform operations:<h3 dir="ltr">Time Savings</h3>The AI-powered Tiny Code Reader streamlines the process of reading and interpreting codes, significantly reducing the time required for tasks that traditionally depend on manual input or slower, less efficient scanning technology. Providing instant, accurate code reading capabilities minimises delays in operational processes, leading to faster turnaround times and increased productivity.<h3 dir="ltr">Reduction of Human Error</h3>Human error in code reading can lead to misinterpretations, incorrect data entry, and subsequent errors. The AI-driven approach of the Tiny Code Reader mitigates these risks by ensuring high accuracy in code interpretation. This improves the reliability of the data collected and enhances decision-making processes based on this data.<h3>Enhanced Quality Assurance</h3>Quality assurance in manufacturing, logistics, and other code-dependent operations is crucial for maintaining standards and customer satisfaction. The precision and consistency of the AI-powered Tiny Code Reader ensure that codes are read and interpreted correctly every time, contributing to higher quality control standards and fewer defects or errors in products and processes.<h3 dir="ltr">Smoother, More Efficient Processes</h3>By automating the code reading process, this device eliminates bottlenecks and inefficiencies associated with manual scanning or older scanning technologies. Its implementation leads to smoother, more streamlined operations where data flow is optimised, and the potential for delays or errors is significantly reduced.<h3 dir="ltr">Improved User Experience</h3>For end-users, the benefits extend to a more seamless interaction with technology, where information is processed quickly and accurately. This can enhance experiences in retail environments, for example, where checkout times are reduced, or in smart home setups, where users can interact more naturally with their devices.The <a href="https://www.himax.com.tw/wp-content/uploads/2022/12/20221222-Useful-Sesnsors-CES_Final.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">collaboration</a> between Useful Sensors and Himax Technologies to bring AI Interfaces for Everyday Objects, incorporating WiseEye technology for smarter device interfaces, highlights the broader applicability and impact of such AI-powered tools in improving daily life and operational efficiencies across sectors.<h2 dir="ltr">Conclusion</h2>The AI-powered <a href="https://www.okdo.com/p/useful-sensors-tiny-code-reader/" target="_blank" rel="noopener noreferrer">Tiny Code Reader by Useful Sensors</a> is a breakthrough in data input and verification, poised to revolutionise how businesses and developers approach these tasks. With its advanced AI capabilities, this device offers a robust solution for interpreting and processing various codes with unparalleled speed and accuracy.&nbsp;Its key features, including natural language processing and the ability to operate without an internet connection, underscore its potential to enhance operational efficiency and data security significantly.The Tiny Code Reader represents an opportunity for businesses and developers to leap forward in efficiency and accuracy. Integrating this technology into operations could streamline processes and open new innovation and service improvement avenues.&nbsp;In conclusion, the advent of the Tiny Code Reader is a testament to the transformative power of AI in enhancing operational workflows and user experiences. Businesses and developers are encouraged to explore how this cutting-edge technology can be adopted into their operations, unlocking new efficiency, accuracy, and innovation levels. The future of data input and verification is here, and it is incredibly efficient, secure, and user-friendly.<h2 dir="ltr">References</h2><ol><li dir="ltr"><a href="https://www.electronicspecifier.com/products/artificial-intelligence/useful-sensors-new-ai-in-a-box-module" target="_blank">https://www.electronicspecifier.com/products/artificial-intelligence/useful-sensors-new-ai-in-a-box-module</a></li><li dir="ltr"><a href="https://finance.yahoo.com/news/himax-useful-sensors-join-forces-080000714.html?guccounter=1" target="_blank">https://finance.yahoo.com/news/himax-useful-sensors-join-forces-080000714.html?guccounter=1</a></li><li dir="ltr"><a href="https://www.himax.com.tw/wp-content/uploads/2022/12/20221222-Useful-Sesnsors-CES_Final.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">https://www.himax.com.tw/wp-content/uploads/2022/12/20221222-Useful-Sesnsors-CES_Final.pdf</a></li><li dir="ltr"><a href="https://www.hackster.io/news/useful-sensors-tiny-code-reader-is-a-privacy-centric-low-cost-scanner-for-2d-qr-codes-104d9229e8c7" target="_blank">https://www.hackster.io/news/useful-sensors-tiny-code-reader-is-a-privacy-centric-low-cost-scanner-for-2d-qr-codes-104d9229e8c7</a></li><li dir="ltr"><a href="https://www.electronics-lab.com/a-glimpse-into-the-future-of-qr-code-reading-with-useful-sensors-tiny-code-reader/" target="_blank">https://www.electronics-lab.com/a-glimpse-into-the-future-of-qr-code-reading-with-useful-sensors-tiny-code-reader/</a></li></ol>

Discover how the AI-powered Tiny Code Reader by Useful Sensors revolutionises data input and verification tasks, offering unparalleled efficiency and accuracy. Explore the benefits for businesses and developers in integrating this cutting-edge technology into their operations.

Unlocking Efficiency: The AI-Powered Tiny Code Reader by Useful Sensors

The global transition to&nbsp;electrified personal transport is gaining momentum, with consumer electric vehicles (EVs) leading the way. According to the International Energy Agency (IEA), EV sales exceeded 10 million units in 2022.That total made up 14 percent of all new cars sold - up from less than 5 percent in 2020[1]. This shift is being driven by a combination of financial incentives and regulations, as governments across the globe commit to an EV future as part of a drive toward “net zero” carbon emissions.&nbsp;But there’s a danger that growth could be stifled by a significant issue: across the globe, EV charging stations lag vehicle sales.&nbsp;<h2>The need for accessible EV charging</h2>In countries where EVs are already popular, there tends to be well developed infrastructure; for example, Norway (where 86 percent of new cars are EVs) and Iceland (72 percent) have widespread charging networks. In contrast, the U.S. is falling behind in EV adoption—with the cars making up only five percent of new sales—removing the commercial incentive for companies to build charging infrastructure.&nbsp;Currently, the number of U.S. EV charging stations falls well below the availability of traditional gas stations, even when considering the size EV fleets compared to gas-powered vehicles. According to&nbsp;Motor.com, the U.S. averages about 104 gas pumps per 1,600 road kilometers, compared to just 22 EV charging ports[2]. The problem is made worse because it takes just minutes to fill a car from a gas pump—making it quickly accessible to the next vehicle in the line—while EV charging is much slower even with the latest generation of fast chargers. &nbsp;&nbsp;<h2>Avoiding flat batteries</h2>The limited availability of charging stations means that the last thing any EV driver needs is poor equipment reliability. Because EV drivers tend to plan road trips around the relatively few available charging stations when the roll up at one, they need it to work. And it’s not just consumers, governments too expect well maintained networks. For example, a new UK law, the&nbsp;Public Charge Point Regulation 2023, requires each charging point to be 99 percent reliable.&nbsp;&nbsp;To keep public charging points functioning that dependably, they need to be continuously monitored so that any problems can be quickly identified and fixed. Better yet, the monitoring could be used to address problems well before they result in equipment failure.&nbsp;&nbsp;Such monitoring requires robust, country-wide, and long-range wireless connectivity to collect data on the availability and condition of charging stations. And the only standards-based technology that can do this is&nbsp;<a href="https://www.nordicsemi.com/Products/Wireless/Low-power-cellular-IoT" target="_blank">Cellular IoT</a>. The technology enables companies to send EV charger data to a Cloud platform for remote analysis and to determine if the charger needs a visit for a service.&nbsp;<h2>Wireless connectivity for home charging</h2>The year-on-year increase in range of EVs promises to make home charging just as significant as public charging because it means that for all but the longest journeys, consumers can top up batteries in their own garage. This private market is made up of a range of individual suppliers, with two main types of home chargers. One type is low-cost and without Internet connectivity; despite the price advantage, this type may become less popular in the future due to inconveniences such as not being able to take advantage of flexible tariffs.&nbsp;The other popular type of home EV charger can access the Internet. The charger can be directly connected using Cellular IoT; alternatively, the charger can access the Internet via home Wi-Fi. With the introduction of the latest version of the wireless tech, Wi-Fi 6, the chargers can be easily integrated into the smart home ecosystem. This is because Wi-Fi is a key constituent of Matter, a smart home standard backed by companies such as Apple, Google, Samsung, and Nordic Semiconductor.&nbsp;&nbsp;As an integral part of the smart home, the domestic EV charger can, for example, ask the owner if a full charge is necessary for tomorrow because on that day of the week the car is usually only driven on short journeys. If a full top-up is asked for, connectivity allows the charger to determine precisely when to switch on charging to take advantage of the cheapest tariff. &nbsp; &nbsp;&nbsp;<h2>EV charging is set to become big business</h2>While public charging infrastructure remains relatively scarce, as EV ownership grows, so will the supporting network. And that will mean hundreds of thousands of chargers spread across entire countries. Cellular IoT is the only LPWAN capable of the coverage and reliability demanded by such huge charging networks. But more than that, cellular IoT brings other benefits.&nbsp;&nbsp;According to report published by telecoms services and equipment provider, Ericsson, connectivity brings significant business opportunities for EV charging companies and the related ecosystem. By connecting charging stations with cellular IoT, EV charging companies are better positioned to effectively manage their orchestration, administration, and maintenance. That in turn keeps the complex ecosystem of stakeholders—including drivers, hardware and connectivity providers, utility companies, automotive OEMs, and asset owners like parking operators, city authorities, and homeowners—satisfied.&nbsp;&nbsp;EV’s promise a greener future. But each driver wants reassurance that when they need to recharge their vehicle’s batteries, a fully functioning charger will only be a short hop away. Wireless technologies like cellular IoT and Wi-Fi will not only make it simple for service providers to keep their chargers in good order but will also help them efficiently and remotely manage huge charger networks. &nbsp;&nbsp;<hr><h3>References</h3>1. Global EV Outlook 2023;&nbsp;<a href="https://www.iea.org/reports/global-ev-outlook-2023/executive-summary" target="_blank">www.iea.org/reports/global-ev-outlook-2023/executive-summary#</a>&nbsp;2. Study explores EV charging vs gas station density in the U.S.;&nbsp;<a href="https://www.motor.com/2023/08/study-explores-ev-charging-station-vs-gas-station-density-in-the-u-s" target="_blank">www.motor.com/2023/08/study-explores-ev-charging-station-vs-gas-station-density-in-the-u-s</a>&nbsp;

The global transition to electrified personal transport is gaining momentum, with consumer electric vehicles (EVs) leading the way. According to the International Energy Agency (IEA), EV sales exceeded 10 million units in 2022.

Improving EV charging networks with cellular IoT

Battery Type: Electrochemistry, Capacity, and Energy DensityConsider the application and device form factor when choosing the battery. Coin cell batteries are compact and suitable for low-power devices with minimal energy needs but have limited capacity and are non-rechargeable. Lithium-ion (Li-ion) or lithium-polymer (Li-poly) batteries offer higher capacity, rechargability, and longer lifespans, making them suitable for devices with higher power demands and longer lifecycles. Customized batteries may be necessary for devices with unconventional form factors.Capacity, measured in mAh or Wh, refers to the amount of charge a battery can store, while energy density relates to the amount of energy stored per unit volume or weight. Selecting a battery with sufficient capacity and energy density ensures extended device operation without frequent battery replacements.Voltage and Discharge CharacteristicsEnsure the battery voltage aligns with the device's voltage requirements over its entire lifespan. Understand the discharge rate influenced by the application's use, such as data transmission frequency, intensity, and duration. These factors impact battery characteristics, including discharge rate and voltage drop over time, ultimately affecting power consumption and runtime.TemperatureTemperature significantly affects battery performance. Extreme temperatures can impact capacity, discharge rate, and lifespan. Select a battery with an operating temperature range suitable for the device's environmental conditions.Battery and Device Shelf LifeConsider battery conditions, such as self-discharge, both before integration into the IoT device and once integrated. Aging and self-discharge affect performance, so understanding these parameters during product development and post-market deployment is crucial.Cost and LifespanEvaluate upfront cost and total cost of ownership over the battery's lifespan. Assess the battery's expected lifespan and balance it with the device's operational duration to optimize cost-effectiveness.By considering these factors, developers can choose the right battery for their IoT devices, ensuring optimal performance, longevity, and cost-effectiveness. Relying solely on data sheets is not sufficient. Further tests need to be done due to the device-specific conditions and batteries. This will be adressed in the following blogpost. If you can’t wait, download the&nbsp;<a href="https://www.qoitech.com/whitepaper/powering-iot-devices/" target="_blank">white paper</a>.

Choosing the appropriate battery for IoT devices is critical to ensure optimal performance and longevity. There are several factors to consider when selecting a battery that aligns with the specific requirements of the application, allowing for reliable and long-lasting power supply.

Choosing the Right IoT Battery

For some IoT products, connectivity failure is a momentary inconvenience. For others, it’s a disaster.Imagine losing temperature data for a shipment of vaccines at a critical moment; there goes your cold chain compliance. Or think of a smart car’s accident detection and alert system. If the driver encounters a problem outside your cellular coverage area, disconnection can create life-threatening delays for responders.Looking forward, universal connectivity will be essential for self-driving vehicles—and a whole universe of yet-to-be-imagined technology. While cellular connectivity is already strong for&nbsp;<a href="https://www.mobileconnectivityindex.com/index.html" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">populated areas and large parts</a> of North America, South America, Europe, and Asia, there are still gaps that affect global operators.The lack of coverage is particularly impactful for the agriculture and maritime industries, in which IoT devices continually move in and out of cellular signals. But for any or all mobile IoT, universal coverage is the ultimate prize. Today, a merger of technologies puts it within reach.The addition of satellite networks to cloud-based cellular connectivity is the key to global coverage. Here’s how satellite-cellular integration can make location-based connectivity loss a thing of the past.&nbsp;<h2>Satellite Non-Terrestrial Networks in Cellular IoT</h2>The simplest, most cost-effective way to keep your IoT deployments connected is with the help of a connectivity partner. These connectivity-as-a-service cloud providers offer access to many cellular networks at once, getting close to a global connection with one SIM and self-service fleet management tools.However, even the most well-connected IoT connectivity provider is limited by mobile network operators (MNOs) themselves. An MNO tends to build towers where lots of people will use them. That doesn’t help in low-population regions or far out at sea. In fact, cellular networks are also called terrestrial networks, because they’re bound to land.Contrast that technology with&nbsp;non-terrestrial networks, or NTNs. These satellite-based connectivity networks fill the coverage gaps left by MNOs. The trouble is, until recently, satellite connectivity required different hardware than its cellular counterpart. It was expensive and space-inefficient to offer both cellular and satellite connectivity in the same device.The solution is a connectivity partner that offers integrated satellite NTN with traditional terrestrial networks—all through the same SIM card.&nbsp;<h2>How to Add Satellite NTN to Your Connectivity Plan</h2>First, look for a connectivity-as-a-service provider that offers seamless satellite NTN within existing cellular plans. Just know that not all your choices offer the same benefits. Choose a connectivity partner that provides the following features in its NTN-integrated service:<ul><li>Automatic network switches.&nbsp;You can’t manage every device’s connection manually. Look for a SIM that automatically connects to the correct cellular or satellite network—and a self-service platform that allows you to define which networks are correct.</li><li>Simple tools for integration with your existing technology stack. You shouldn’t have to hire a team of developers to bring satellites into your connectivity portfolio. Choose a partner that ships ready-to-use APIs for quick, low-stress integration.</li><li>Compatibility with 3GPP low-power, wide area network (LPWAN) technologies. You shouldn’t have to sacrifice access to cellular technologies optimized for IoT just to incorporate your NTN. A specification like NB-IoT gives advantages like a small form factor and limited price; choose a connectivity source that bundles NB-IoT or other IoT LPWAN with satellite coverage.</li><li>Pay-as-you-go connectivity. Price has long been the key barrier to satellite IoT. With a pay-as-you-go model, you don’t pay for the satellite data you don’t use—and you can access satellite networks for as little as $1.00 per kilobyte.</li><li>A combined NTN/cellular SIM card. The other price challenge associated with satellite IoT is the module, which can easily run several thousand dollars per unit. With the right connectivity partner, you can access NTN&nbsp;and global cellular networks with the same SIM card.</li></ul>&nbsp;Satellite integration is becoming increasingly more accessible for IoT developers, and the simplest way to access this technology is to find the right partner. This industry development will help fill connectivity gaps for global deployments—and might be the key to transformative new use cases for mobile IoT in general. Every IoT developer should be aware of this powerful tool in the connectivity toolkit.

For some IoT products, connectivity failure is a momentary inconvenience. For others, it’s a disaster.

IoT Everywhere: How Satellite-Cellular Integration Enables Universal Connectivity

In the ever-evolving landscape of agriculture, the integration of technology has proven to be a game-changer. One of the most transformative advancements in recent years is the widespread adoption of the Internet of Things (IoT), which has revolutionized traditional farming practices and given rise to the era of smart agriculture. With a particular focus on harnessing the power of mobile connectivity and private 5G networks, farmers worldwide are now equipped with cutting-edge tools to optimize efficiency, increase yields, and ensure sustainable practices.&nbsp;<h2>The Connected Fields</h2>IoT’s impact on agriculture lies in its ability to interconnect various devices and sensors across farmlands, creating an intelligent network that provides real-time data and insights. Farmers can monitor crucial variables like soil moisture, temperature, and crop health remotely, allowing for timely decision-making and resource allocation. This connectivity is further enhanced by the widespread use of mobile networks, enabling farmers to access critical information on their smartphones or tablets, regardless of their physical location.&nbsp;<h2>Unleashing the Power of 5G</h2>The advent of 5G technology has taken smart agriculture to new heights, providing farmers with faster, more reliable, and low-latency connectivity. Private 5G networks, specifically tailored for individual (and often remote) farms, offer a dedicated and secure communication channel. This ensures that the vast amount of data generated by IoT devices is transmitted seamlessly, facilitating quick response times and reducing the risk of interference.&nbsp;<h2>Precision Farming at its Best</h2>One standout application of IoT in agriculture is precision farming, where data-driven insights enable farmers to optimize resource utilization. With the help of IoT devices, farmers can precisely control irrigation systems, monitor crop growth, and even deploy drones for aerial surveys. The integration of 5G ensures that these devices can communicate in real-time, allowing for swift adjustments based on the evolving conditions of the field.&nbsp;<h2>Sustainable Agriculture Practices</h2>Smart agriculture isn’t just about maximizing yields; it’s also about sustainability. IoT devices enable farmers to implement precision pesticide and fertilizer applications, reducing environmental impact and minimizing waste. The efficiency gains achieved through IoT-driven practices contribute to the overall sustainability of agriculture, aligning with global efforts to address climate change and environmental concerns.&nbsp;<h2>A Global Impact</h2>The impact of IoT-enabled smart agriculture is felt across the globe. From large-scale commercial farms to smallholder operations, the adoption of these technologies is transforming the way food is produced. Developing countries, in particular, stand to benefit as these technologies enhance productivity, reduce risks, and empower farmers with tools that were once only available to their more resource-rich counterparts.In conclusion, the marriage of IoT and mobile connectivity, amplified by the capabilities of private 5G networks, is reshaping agriculture into a smarter, more efficient, and sustainable industry. As the world grapples with the challenge of feeding a growing population, these technologies provide a beacon of hope, offering farmers the tools they need to navigate the complexities of modern agriculture and cultivate a bountiful future.

In the ever-evolving landscape of agriculture, the integration of technology has proven to be a game-changer. One of the most transformative advancements in recent years is the widespread adoption of the Internet of Things (IoT).

Harvesting the Future: IoT Cultivating Smart Agriculture with Mobile Connectivity and Private 5G Networks

<h2 id="isPasted">What Is a Smart Factory?</h2>A smart factory is a factory that achieves operational process improvements, higher quality, and lower costs based on digital data by connecting processes from design to development, manufacturing, and maintenance in a network. In the manufacturing industry, it refers to automating various processes in a factory to realize product quality and productivity improvements, a reduction in manufacturing costs, a shortening of the commercialization, mass production and delivery periods, and other areas of improvement. In other words, a smart factory is a factory working on digital transformation (DX) that aims to transform the entire business process from design to manufacturing, maintenance, and logistics in addition to improving productivity by automating factory equipment.We introduce here the results of a questionnaire survey* we conducted with people involved in promoting the conversion of regular factories into smart factories in the manufacturing industry in Japan.*About the Questionnaire Survey Organization conducting the survey: Murata Manufacturing Co., Ltd. Survey targets: 11,084 workers in the manufacturing industry in Japan (screening survey) and 500 people working in the manufacturing industry who are involved in converting regular factories into smart factories in their companies (main survey) Survey method: Internet survey Survey period: Three days from January 25 (Wed.) to 27 (Fri.), 2023 *Total figures may not match due to rounding.<h3>State of Progress in Converting Regular Factories into Smart Factories</h3>We learned that over 38% of factories are in the process of converting into smart factories or considering converting into a smart factory in the questionnaire we conducted this time (Fig. 1). We can see a trend for even more companies to convert their regular factories into smart factories in the future.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5NTg1NzUzLWltZzAwMDFfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 1: Situation concerning the conversion of regular factories into smart factoriesMoreover, the most common reason for converting regular factories into smart factories is to improve productivity. The next most common reason is to reduce costs (Fig. 2).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5NjU1OTgxLWltZzAwMDJfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 2: Reasons for converting regular factories into smart factories<h3 id="isPasted">Main Factors Behind Inability to Promote the Conversion of Regular Factories into Smart Factories</h3>On the other hand, the following are given as the main factors behind the inability to promote conversion of regular factories into smart factories: following on from the understanding of top management, the establishment of specialist teams, the acquisition and training of specialist human resources, cooperation with external partners and other human resources and know-how shortage issues (Fig. 3).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5Njg1NDc4LWltZzAwMDNfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 3: Main factors behind inability to promote the conversion of regular factories into smart factoriesIn addition, we learned that even factories working to convert into smart factories are suffering setbacks in terms of data analysis and prediction and data collection and accumulation (Fig. 4).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5NzA2MzM1LWltZzAwMDRfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 4: Steps where setbacks are being suffered in the conversion of regular factories into smart factoriesIt is thought that how to overcome these steps will be the key to promoting the conversion of regular factories into smart factories. We will consider these issues using the example of short stoppages, which are one type of equipment loss that are a major factor adversely affecting the productivity of smart factories, from here onward.<h2>Short Stoppages: Blind Spot in the Conversion of Regular Factories into Smart Factories</h2>Equipment loss arising in each process is a major issue that must be resolved for the conversion of regular factories into smart factories that greatly contributes to improving productivity in factories.The types of equipment loss include stoppage losses resulting from failures, setup changes, jig replacements and startup, defective product losses, speed reduction losses, and short stoppage losses. In particular, short stoppages are called idling losses and are losses included in the time when, in principle, the equipment could be demonstrating its performance (net operating time) (Fig. 5).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5NzI4Nzg2LWltZzAwMDVfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 5: Equipment loss times and types<h3 id="isPasted">Short Stoppages: Unseen Equipment Loss Lurking in Manufacturing Lines</h3>Setup change, jig replacement, and startup losses are planned. In addition, as it takes a long time to recover from failure losses, we keep a record showing the operational status. However, short stoppages occur unexpectedly on the line and workers at the worksite recover from it and resume work in a short time. The shortness of this time until recovery means that a record of these short stoppages is not kept in most cases. Furthermore, even if attempts are made to keep records of short stoppages, there is currently no time to do so because a speedy recovery is sought.If we do not record the time of a short stoppage, the operating rate is calculated without including that time. Accordingly, a difference arises with the actual operating rate. Furthermore, the cause of long equipment stoppages such as failure losses may be lurking in short stoppages. It is possible to see cases in which problems in the operating rate due to such short stoppages are overlooked even in factories that have been converted into smart factories.<h3>Does Converting Regular Factories into Smart Factories Produce Short Stoppages?</h3>Many industrial robots and automatic machines are installed in the manufacturing lines of smart factories. These comprise precision components. It is not possible to avoid a decline in their precision due to the usage burden and degradation over time. If the precision of these components declines, malfunctions may occur. For example, an industrial robot may fail to grip work or a deviation may arise in the trajectory of a robot arm and it may not be possible to move the part equivalent to the fingers of the robot called the end effector to the correct position. Such malfunctions may cause short stoppages.<h2>Reasons Why Short Stoppages Are Not Eliminated and Countermeasures</h2>Why are short stoppages, which cause various problems in factories in addition to obstructing improvement in productivity, not eliminated? The reason is that in the midst of frequent short stoppages on a daily basis, there is an atmosphere in which manufacturing worksites do not take the situation seriously.The most effective way to prevent such a situation is to calculate and visualize the losses from short stoppages. However, we would need to enter the process, cause, and equipment stoppage time on a worksheet each time such a short stoppage occurs and then aggregate that data to calculate it, which would interfere with production. Moreover, it is difficult to identify the cause of short stoppages by collecting data once a week or once a month.We obtained results from the questionnaire showing that standardization and visualization using digital technologies and optimization of equipment maintenance with sensors and AI are effective ways of resolving such problems in factories which have been successful in promoting their conversion into smart factories (Fig. 6).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5NzUwNzg4LWltZzAwMDZfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 6: Initiatives in promoting the conversion of regular factories into smart factories<h2 id="isPasted">Clues to Reducing Short Stoppages</h2>We need data on the operating status of equipment to reduce short stoppages. For that, we must be able to accurately and quickly record the equipment stoppage times due to the frequent short stoppages and their causes. We introduce here the m-FLIP solution tool that helps to resolve such issues.<h3>What Is m-FLIP?</h3>m-FLIP is a solution that combines Murata Manufacturing’s worksite improvement know-how and IT technologies to maximize the operating rate of manufacturing devices. This solution makes it possible to quantify factors such as operating rate, actual working rate, and equipment stoppages to increase production and achieve optimal maintenance. This greatly contributes to the visualization of problems that are difficult to reveal such as short stoppages.Furthermore, m-FLIP calculates and outputs the operating rate and actual working rate based on data obtained from PLCs made by multiple manufacturers. In addition, it collects workers’ work information through touch-panel PCs. As a result, we can clarify the duration and number of equipment stoppages, which was previously done by guesswork. We are also able to clearly see the main causes of equipment stoppages and the issues that must be resolved (Fig. 7).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5Nzc2NTU0LWltZzAwMDdfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 7: Services provided by m-FLIP<h3 id="isPasted">m-FLIP Utilization Examples</h3>m-FLIP can support the resolution of various issues at manufacturing worksites. We introduce here some typical utilization examples.<h4>Equipment maintenance:</h4>With checks by humans, it is only possible to monitor the operating status temporarily. However, m-FLIP can continuously monitor the operating status of equipment. It is possible to continuously collect data over several months or several years. This allows us to grasp the aging and changes over time of equipment. As a result, it enables maintenance at the optimal timing while minimizing the impact on the operating rate to the greatest possible extent.<h4>Quality control:</h4>For example, it is possible to monitor static electricity generation status based on data from temperature sensors and humidity sensors around the equipment and to output an alert when the set threshold is exceeded. We can utilize this in quality control such as to prevent the outflow of defective products. Moreover, we can also collect data including information on vibrations, current, and voltage. We can then integrate the data we have obtained from multiple sensors and output it as a single piece of information.<h4>Work procedure review, equipment improvement, and personnel allocation optimization:</h4>We can grasp the movements of workers and the operating status of equipment as quantified information. Therefore, we can also utilize it to consider work procedure reviews, equipment improvements, and personnel allocation optimization.<h4>Preparation of reports:</h4>m-FLIP comes with a function to prepare reports that can be used for reporting (Fig. 8). You can display information in charts and tables. It is also possible to input and save comments. You can share the reports you have prepared.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5ODAwNTEwLWltZzAwMDguanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 8: Monthly report screen<h4 id="isPasted">After-sales support by professionals:</h4>After introducing m-FLIP, we can identify issues from the data we have collected and receive suggestions for improvements and other advice from professionals familiar with production technologies, factory technologies, and other technologies.<h2>m-FLIP Introduction Case Study (Example of Ogaki Murata Manufacturing)</h2>We now introduce a case study from Ogaki Murata Manufacturing in which they resolved frequently occurring problems including short stoppages due to tray replacement in the product-washing process and short stoppages due to component adhesion errors with the m-FLIP operating rate improvement solution tool.<h3>Pursuit of the Causes</h3>We intuitively knew that short stoppages were occurring in the tray/rack refilling machine at the manufacturing worksite. However, we were not able to quantify the stoppage time or the number of stops. Accordingly, we collected data on the tray/rack refilling machine and the component adhesion device with m-FLIP. We uncovered the following problems as a result. ・Non-operation due to waiting for tray replacement: 12% ・Non-operation due to adhesion errors: 8%<h3>Improvement 1: Reduction in the Tray Replacement Time</h3>We now display on ANDON the number of trays remaining until the completion of the tray replacement (Fig. 9). We display in ANDON the timing of the tray replacement before the work of refilling the product into the tray is complete. This has meant we have been able to greatly reduce the time spent waiting for tray replacement.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5ODIxMDM5LWltZzAwMDkuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 9: Countdown ANDON that predicts the equipment work completion<h3 id="isPasted">Improvement 2: Resolution of Short Stoppages</h3>We analyzed in detail the contents of the short stoppages. As a result, we ascertained that 80% or more of the short stoppages were component adhesion errors (Fig. 10 and Fig. 11).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5ODQyMjMyLWltZzAwMTBfZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Fig. 10: Breakdown of the equipment operating rate and non-operating rate items<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTI5ODU2NjE4LWltZzAwMTBhLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Fig. 11: Operating status Gantt chartWe found that the cause of the component adhesion errors was changes in the clearance between the product adhesion nozzle and product due to changes over time in the washing rack jig. As a countermeasure, we shortened the gap between the adhesion nozzle and the product. This allowed us to significantly reduce short stoppages due to adhesion errors.In this way, it is first necessary to digitize the operating status of equipment and the behavior of workers to improve short stoppages. We can pursue the causes of short stoppages by analyzing and parsing the data we collect.<h2>Summary</h2>This questionnaire revealed issues in the conversion of regular factories into smart factories and challenges in promoting that in numerical data. We can see that quantifying and visualizing the various losses lurking in production lines is essential for improving productivity from these results. We focused on the theme of short stoppages this time. However, quantified data is also indispensable to resolve other issues in the conversion of regular factories into smart factories. The questionnaire results show that this requires high density and quality of the data to be collected as well as analytical skills.<hr id="isPasted"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711016095493-1711016095493.png" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don't hesitate to reach out. There's an entire team ready to support you with your question.<a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a>

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Monogoto

AVSystem

IoT Stars

rinf.tech

Introduction

Edge AI Market Analysis and Trends

Healthcare and Medical Applications

Industrial IoT and Manufacturing

Smart Cities and Urban Infrastructure

Retail and Customer Experience

Energy Efficiency and Sustainability

Agriculture and Food Production 

Automotive and Transportation

Generative AI at the Edge

Edge AI Challenges and Real-World Mitigations

The Future of Edge AI

Exploring the Dynamic World of Edge AI Applications Across Industries


2024 State of Edge AI Report

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Network System Control Center Operator Working

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An engineer using SCADA to monitor and control industrial processes via PLC.

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IoT

2024 State of Edge AI Report

Introduction

1. Edge AI Market Analysis and Trends

2. Healthcare and Medical Applications

3. Industrial IoT and Manufacturing

4. Smart Cities and Urban Infrastructure

5. Retail and Customer Experience

6. Energy Efficiency and Sustainability

7. Agriculture and Food Production

8. Automotive and Transportation

9. Generative AI at the Edge

10. Edge AI Challenges and Real-World Mitigations

11. The Future of Edge AI

Internet of Things: A Comprehensive Guide to its Engineering Principles and Applications

Profiles