How the Internet of Things (IoT) is used in modern AI applications

June 7, 2022 | 115 views

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Artificial intelligence (AI) has already made headway into becoming a general-purpose technology vastly impacting economies. Yet, the interpretation and estimated trajectory for something remotely close to what we call AI now was first explored in the 1950s.

Until this very day, AI keeps on evolving further. Though let’s face it, AI would have been useless without data. With around 2.5 quintillion bytes of data being generated every day, the numbers will shoot up as the Internet of Things (IoT) enters the game.

Let’s see what this is all about and where and how exactly IoT crosses paths with AI applications.
  • IoT fundamentals: Where does IoT meet AI
  • The benefits of IoT in AI
  • Challenges of IoT in AI
  • Why implement machine learning in IoT
  • IoT applications for AI
  • Key takeaways

IoT fundamentals: Where does IoT meet AI?
What is meant by the term internet of things (IoT) is essentially a system of correlated digital and mechanical appliances, computing devices, and sensors embedded often into everyday objects that transfer data over a network. IoT connects the internet to any and every physical thing or place in the world.

Modern IoT has advanced from the mere merging of microelectromechanical systems to wireless technologies, and faster data transfer through the internet. This resulted in a confluence of information technology and artificial intelligence, allowing unstructured machine-generated data to be evaluated for insights that could lead to new developments.

More and more industries are now referring to IoT to function more proficiently, provide better customer service, escalate the significance of their business, and implement robust decision-making.

Machine learning for IoT can be used to identify anomalies, predict emerging trends, and expand intelligence through the consumption of audio, videos, and images. The implication of machine learning in IoT can substitute manual processes and offer automated systems using statistically backed up actions in critical processes.

The benefits of IoT in AI and real life
IoT offers the following benefits to AI applications:
  • IoT data for business purposes
  • Cost and time savings
  • Task automation and reduction of human intervention
  • Higher quality of life

IoT data for business purposes
IoT can also be viewed as a data pool. That means by aggregating IoT data, one can extract useful data-driven feedback, which in turn (used properly) may foster effective decision-making. Businesses can also identify new market opportunities, not because of IoT itself but by using the data IoT provides. And since IoT offers companies access to more data, and hence advanced analytics of that data, its usage can eventually result in improved customer outcomes and enhanced service delivery.

Cost and time savings
When devices get connected, cost reductions come along with it. The gathering of different data allows for advances in efficiency, and it leads to money surplus and low-cost materials.

Task automation and reduction of human intervention
Nowadays, devices that are internet-connected can be found in every aspect of our lives, and it is safe to say that they make tasks easier. These automation features range from real-time AI-powered chatbots to home automation control systems, and all of it usually takes a click of a button.

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Higher quality of life
IoT is not only beneficial in the business aspects but it also creates better living circumstances for us. Smart cities and agriculture, intelligent homes, and food waste solutions are some of the most common ways of IoT providing better, more sustainable living conditions for people.

Challenges of IoT in AI
Despite the numerous benefits and advancements that IoT brings to the table, there have been a few limitations with it. Some of them are listed below:
  • Privacy issues
  • Data overflow
  • Bug issues
  • Compatibility issues

Privacy issues

With the increased connection between multiple devices or their coexistence for model development purposes, more information is shared between them, which poses vulnerability to your data and makes room for caution. Added layers of protection are needed to prevent risks of data leaks and other threats.

Data overflow
Eventually, organizations will have to find a way to deal with the large numbers of IoT devices, and that will include the collection and systematic management of all the data from those IoT devices. The proper use of data lakes and warehouses, close governance, and intuitive arrangement of datasets will become an utmost priority.

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Bug issues
If one IoT device has a bug in its system, there is a large chance that every other connected device will also have it.

Compatibility issues
Because there are no international standards of compatibility for IoT, it's harder for different devices to communicate with one another.

Why implement machine learning in IoT
More and more companies are combining IoT with machine learning projects so they can achieve analytical skills on a large variety of use cases which allows their businesses to have access to fresh insights and adopt innovative automation. By implementing machine learning for IoT, they can leverage the following:
  • Convert data into a coherent format
  • Arrange the machine learning model on device, edge, and cloud
  • Enable use of data on edge devices directly for complex decision making

IoT applications for AI
Although we have covered the basics of IoT, its implications for AI are not as simple. Many corporations are adopting IoT which allows them to have an advanced approach to growing and advancing their business. Novel IoT applications are offering organizations the ability to plan and implement more vigorous risk management strategies. Some of the more common uses of IoT in AI encompass the following:

Transport logistics
Not only does IoT expand the material flow systems in transport logistics, but it also improves the automatic identification and global positioning of freight. It also increases energy efficiency and consequently declines the consumption of energy.

Smart cities
Although the term smart city is still incomplete, it mainly refers to an urban area that endorses sustainable enlargement and high quality of life. Giffinger et al.’s model explains the features of a smart city, including the people, the government, the economy, and lifestyle.


E-health control
The two main objectives of future health care are e-health control and prevention. People nowadays can choose to be monitored by physicians even if they do not live in the same country or place. Tracing and monitoring peoples’ health history makes IoT-assisted e-health extremely useful. IoT healthcare solutions could also benefit the specialists, as they can collect information to advance their medical calculations.

Key takeaways
Ever since its development, IoT, especially AI-enabled IoT, as discussed, has been enhancing our daily lives and directing us to work smarter while having complete control over the process. Besides having smart appliances to elevate homes, IoT devices can also be essential for providing insights and an actual look for businesses into their systems. Heading forward, IoT will continue to develop as more organizations get to understand its potential usage and tangible benefits.

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What Impact Will Data Management Have on Your IoT Strategy?

Article | July 19, 2022

For businesses to grow, they must be armed with the right technology and implement the right strategies to get a high return on their investments. With an IoT strategy, you can successfully make sense of the high volumes of data generated. IoT is about having devices with sensors communicate with other devices over the internet and share real-time data or parameters to maintain healthy system processes. Sharing and transferring data in real time over the cloud creates a lot of data that needs to be carefully managed. Not having a streamlined method to control and manage the volume of data to capture, send, transmit, and receive over the cloud poses many space constraints as the data piles up quickly. Furthermore, deciding what data to keep and what to discard, how long you need the data, and for what purpose are all critical. Some standard IoT devices include sensors, lights, alarms, and cameras that a smartphone can control. 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Creating a better product is essential to add more value to your product offerings and avoid recalls, keeping your brand reputation at stake. The more data, the deeper the analysis, and the more refined the product, the greater the need to manage large amounts of data efficiently. The future of IoT data management is promising when it comes to improving all aspects of your business processes, mainly controlling the automation and manufacturing processes and software triggers. Check out the in-depth benefits of data management in IoT. Data management in IoT helps conduct a field test of your IoT products before deployment. Improve the uptime of your business production lines and equipment. Perform seamless decision-making for planning, scheduling, and execution systems to meet the changing customer and market demands using accurate and current data. Data management helps efficiently deploy IoT solutions such as enterprise resource planning (ERP), enterprise asset management (EAM), and manufacturing execution systems (MES) in manufacturing businesses. Data management helps remote monitoring of automation systems and robotic systems in industrial IoT needs current data and management. Improve production flexibility and responsiveness by welcoming smart manufacturing using IoT data management. When it comes to the data management of IoT devices, different types of data management systems take care of structured and unstructured data. 8 Data Management Systems for Your Enterprise IoT Devices IoT device management means registering, organizing, monitoring, and remotely managing IoT-connected devices at scale. Various cloud architectures with different data management systems help with efficient IoT device management. In addition, equipment data, sub-meter data, and environmental data help track the performance of your IoT devices through IoT data collection. Let's find out how data management systems for IoT devices would help develop an IoT strategy for your large enterprise. IoT gateway device management involves many steps in keeping your operations healthy and maximizing uptime. These are provisioning, authentication, configuration, control, monitoring, diagnostics, software updates, and maintenance. In addition, data management systems aim to make data available for analysis in the long term. The different data management systems are as under: Querying Production Collection Aggression/Fusion Delivery Pre-processing Storage, updating and archiving Processing or analysis. These data management systems capture, organize, store, retrieve, and analyze data when required. Sorting out the data management in IoT will initiate your internet of things database scalability. 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Filtering out valuable data and compressing it accordingly helps seamless data transfer. It is also a part of data collection. • Aggression or fusion: Part of the aggression is real-time data transmission across the network to increase the rate of data streaming over the limited bandwidth. It pulls together information from different points of contact and reduces the amount of information that needs to be stored and sent. • Delivery: Collating the data from multiple touch points across the IoT framework and summing it up for the final responses is a part of the data delivery management system. Making data ready for permanent data storage is also a part of it. • Preprocessing: Removing redundant, missing, and incomplete data and making all the data unified is a part of preprocessing. Data cleaning is also one of the preprocessing methods applied to data mining. • Storage, Update, and Archiving: Storing data in an organized way for long-term offline usage or big-data systems is a part of the storage data management system. It can be decentralized or centralized as per the required capabilities. • Processing or Analysis: Retrieval of stored packets of data accessed for an efficient analysis is a part of data processing or analysis in a data management system. Whenever handling large amounts of data, an efficient data management system will solve numerous problems concerning your IoT strategy, as discussed above. Find out exactly what can keep you from implementing IoT. 5 Growth Challenges in Data Management for IoT Technology High Initial and Ongoing costs: Upgrading the hardware and software infrastructure that is already in place, hiring IoT-trained staff, and building an IoT infrastructure will all require upfront and ongoing costs. Vulnerability: Your IoT security strategy is a critical aspect of your IoT platform strategy. Multiple data points for structured and unstructured data captured, transmitted, stored, and retrieved by software come with security risks. Procuring Quality Hardware: Finding compatible hardware for your requirements and building an infrastructure around them can take a while regarding decision-making for scalability. In addition, hardware must remain supportive of the quick adoption of future software innovations. Installation and Upkeep of Hardware Infrastructure: Setting up a complex IoT strategy with the implementation of IoT data management, infrastructure, security, and more takes time and expertise. One of the other big worries is keeping the hardware infrastructure in good shape so that security can't be broken. Constraints on Scalability and Agility: The humungous IoT data traffic poses a severe concern for appropriate control of the data storage, retrieval, analysis, monitoring, and everything aligned with IoT data management. Also, the fact that IoT data doesn't last as long as other types of data is a risk to the way data flows and is collected. Now, let us figure out how to implement IoT that aligns with your business objectives. How to Implement IoT in Line with Your Business Goals A complete analysis of your immediate and long-term business objectives is critical as it helps decide which data to keep and which to discard after how much time. Every byte of data you hold and analyze comes with a cost for storage, retrieval, and security, which can be a barrier to implementing IoT for your business. Identifying IoT data collection helps you align your IoT implementation strategy with your business objectives. Here are a few ways to address your implementation of IoT. 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Article | February 10, 2020

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Growth Opportunities for Sensors Enabling IoT in Retail

ReportLinker | November 25, 2022

Reportlinker.com announces the release of the report "Growth Opportunities for Sensors Enabling IoT in Retail" However, sensors as a standalone device would not be able to play a vital role in the IoT space as only partial data would remain. Hence, enabling technologies that assist data collection and analysis are necessary to generate meaningful information. Retail IoT includes technologies that collect data (sensors) and those that integrate sensors and facilitate a more immersive retail customer experience. The IoT in retail will primarily transform supply chain management (SCM) and customer engagement opportunities. With the need for the end-to-end traceability of goods and services in retail SCM increasing, and end users having high expectations of an immersive customer experience, it is imperative that retail industry participants across the value chain integrate IoT capabilities to compete. The scope of this research study is limited to technologies that enable an interactive and immersive customer experience. The study assesses emerging technologies that facilitate a personalized customer experience in the retail industry, including sensors, RFID, Bluetooth, Wi-Fi, advanced display, smart lighting, robotics, VR/AR, data analytics, and IoT-based payment technologies, such as NFC. Questions the Research Addresses:What are the main enabling technologies transforming IoT in retail?What are the key factors influencing adoption in the innovation ecosystem? What are the key industry initiatives? Who are the main participants impacting technology development?What are the patent and funding trends in the retail IoT space?What are the future growth opportunities for market participants? About Reportlinker ReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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SORACOM Applies for Listing on the Tokyo Stock Exchange

SORACOM | November 23, 2022

KDDI CORPORATION and SORACOM, INC, a global provider of advanced IoT connectivity services, today announced that SORACOM has applied to list its shares on the Tokyo Stock Exchange. Soracom joined the KDDI Group in August 2017. Since then, Soracom has grown its IoT connectivity platform to support over 5 million IoT connections* for more than 20,000 customers worldwide in industries ranging from energy and manufacturing to payments, consumer electronics, healthcare, and agriculture . From day one, Soracom has made its mission to deliver a global connectivity platform that accelerates speed to market for the teams building tomorrow’s connected world and helps them to pursue success at any scale. To further accelerate its own business growth and global expansion, Soracom began preparation for a potential public offering in 2020. KDDI and SORACOM describe this as a “swing-by” IPO, in which a startup grows with the support of a larger company prior to public offering, as if a space probe accelerates using the gravitational mass of a planet. With appropriate corporate governance systems now in place and demonstrated capacity for independent management, Soracom has now applied to list its shares on the Tokyo Stock Exchange. Prior to any such listing, it is necessary to obtain listing approval from the Tokyo Stock Exchange and complete examination by the Japan Exchange Regulation. This application does not establish any specific commitments regarding listing availability or timing. This press release has been prepared for the sole purpose of publicly announcing that the Company has applied to list its shares on the Tokyo Stock Exchange, and not for the purpose of soliciting investment or engaging in any other similar activities within or outside Japan. This press release does not constitute or form a part of any offer or solicitation to purchase or subscribe for securities in the United States. Any securities may not be offered or sold in the United States absent registration or an exemption from registration under the U.S. Securities Act of 1933. If any public offering of securities is made in the United States, it will be made by means of an English language prospectus prepared in accordance with the U.S. Securities Act of 1933.

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Robustel 5G IoT EDGE Computing Gateway certified by Microsoft Azure and Amazon Web Services (AWS)

Robustel | November 23, 2022

Robustel's latest IoT device the EG5120 5G Edge Computing Gateway is now listed in the Microsoft Azure certified device catalogue and also Amazon Web Services (AWS) IoT Greengrass. The EG5120 helps to seamlessly extend Azure & AWS based IoT cloud services and intelligence to the network edge, and allows customers using Azure and AWS to quickly & seamlessly deploy IoT applications in verticals including autonomous driving, smart cities, industrial IoT (IIoT), smart energy, robotics, and more. With Azure IoT and AWS IoT Greengrass, customers can securely connect, configure, manage, monitor and maintain edge devices and customize applications for field devices, including streaming analytics, machine learning, image recognition and other high-value AI applications that are deployed from the cloud to the edge for local execution, to dramatically reduce the time and cost of connecting various sensors and devices from the edge to the cloud. Features of the EG5120 Robustel 5G Edge Computing Gateway Cutting-edge (Release 16) 5G connectivity. Global cellular band coverage. High performance processor for running complex applications. 2 X RS232/RS485 serial ports for connecting to industrial devices. 2 X Digital Inputs (DI) and 2x Digital Outputs (DO) for simple monitoring and control. Dual SIM card slots for failover & redundancy. Wide operating temperature range, ideal for industrial applications. Linux Debian 11 (bullseye) based Operating System Support for Docker containers for rapid application deployment Access to more than 50,000 applications from the Debian repository. Access to Industrial VPN protocols like Wireguard, IPsec and OpenVPN. Full Modbus TCP and RTU support for industrial data collection. Robustel's management platform RCMS for effective management of large fleets of devices. About Robustel: Robustel are a Wireless IoT & WAN Edge solutions provider specialising in 5G, 4G/LTE & LPWAN devices, helping the enterprise in smart cities, transportation, smart water, energy and precision agriculture industry to deliver unbreakable connectivity by Robustel's hardware and cloud.

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Growth Opportunities for Sensors Enabling IoT in Retail

ReportLinker | November 25, 2022

Reportlinker.com announces the release of the report "Growth Opportunities for Sensors Enabling IoT in Retail" However, sensors as a standalone device would not be able to play a vital role in the IoT space as only partial data would remain. Hence, enabling technologies that assist data collection and analysis are necessary to generate meaningful information. Retail IoT includes technologies that collect data (sensors) and those that integrate sensors and facilitate a more immersive retail customer experience. The IoT in retail will primarily transform supply chain management (SCM) and customer engagement opportunities. With the need for the end-to-end traceability of goods and services in retail SCM increasing, and end users having high expectations of an immersive customer experience, it is imperative that retail industry participants across the value chain integrate IoT capabilities to compete. The scope of this research study is limited to technologies that enable an interactive and immersive customer experience. The study assesses emerging technologies that facilitate a personalized customer experience in the retail industry, including sensors, RFID, Bluetooth, Wi-Fi, advanced display, smart lighting, robotics, VR/AR, data analytics, and IoT-based payment technologies, such as NFC. Questions the Research Addresses:What are the main enabling technologies transforming IoT in retail?What are the key factors influencing adoption in the innovation ecosystem? What are the key industry initiatives? Who are the main participants impacting technology development?What are the patent and funding trends in the retail IoT space?What are the future growth opportunities for market participants? About Reportlinker ReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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ENTERPRISE IOT

SORACOM Applies for Listing on the Tokyo Stock Exchange

SORACOM | November 23, 2022

KDDI CORPORATION and SORACOM, INC, a global provider of advanced IoT connectivity services, today announced that SORACOM has applied to list its shares on the Tokyo Stock Exchange. Soracom joined the KDDI Group in August 2017. Since then, Soracom has grown its IoT connectivity platform to support over 5 million IoT connections* for more than 20,000 customers worldwide in industries ranging from energy and manufacturing to payments, consumer electronics, healthcare, and agriculture . From day one, Soracom has made its mission to deliver a global connectivity platform that accelerates speed to market for the teams building tomorrow’s connected world and helps them to pursue success at any scale. To further accelerate its own business growth and global expansion, Soracom began preparation for a potential public offering in 2020. KDDI and SORACOM describe this as a “swing-by” IPO, in which a startup grows with the support of a larger company prior to public offering, as if a space probe accelerates using the gravitational mass of a planet. With appropriate corporate governance systems now in place and demonstrated capacity for independent management, Soracom has now applied to list its shares on the Tokyo Stock Exchange. Prior to any such listing, it is necessary to obtain listing approval from the Tokyo Stock Exchange and complete examination by the Japan Exchange Regulation. This application does not establish any specific commitments regarding listing availability or timing. This press release has been prepared for the sole purpose of publicly announcing that the Company has applied to list its shares on the Tokyo Stock Exchange, and not for the purpose of soliciting investment or engaging in any other similar activities within or outside Japan. This press release does not constitute or form a part of any offer or solicitation to purchase or subscribe for securities in the United States. Any securities may not be offered or sold in the United States absent registration or an exemption from registration under the U.S. Securities Act of 1933. If any public offering of securities is made in the United States, it will be made by means of an English language prospectus prepared in accordance with the U.S. Securities Act of 1933.

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Robustel 5G IoT EDGE Computing Gateway certified by Microsoft Azure and Amazon Web Services (AWS)

Robustel | November 23, 2022

Robustel's latest IoT device the EG5120 5G Edge Computing Gateway is now listed in the Microsoft Azure certified device catalogue and also Amazon Web Services (AWS) IoT Greengrass. The EG5120 helps to seamlessly extend Azure & AWS based IoT cloud services and intelligence to the network edge, and allows customers using Azure and AWS to quickly & seamlessly deploy IoT applications in verticals including autonomous driving, smart cities, industrial IoT (IIoT), smart energy, robotics, and more. With Azure IoT and AWS IoT Greengrass, customers can securely connect, configure, manage, monitor and maintain edge devices and customize applications for field devices, including streaming analytics, machine learning, image recognition and other high-value AI applications that are deployed from the cloud to the edge for local execution, to dramatically reduce the time and cost of connecting various sensors and devices from the edge to the cloud. Features of the EG5120 Robustel 5G Edge Computing Gateway Cutting-edge (Release 16) 5G connectivity. Global cellular band coverage. High performance processor for running complex applications. 2 X RS232/RS485 serial ports for connecting to industrial devices. 2 X Digital Inputs (DI) and 2x Digital Outputs (DO) for simple monitoring and control. Dual SIM card slots for failover & redundancy. Wide operating temperature range, ideal for industrial applications. Linux Debian 11 (bullseye) based Operating System Support for Docker containers for rapid application deployment Access to more than 50,000 applications from the Debian repository. Access to Industrial VPN protocols like Wireguard, IPsec and OpenVPN. Full Modbus TCP and RTU support for industrial data collection. Robustel's management platform RCMS for effective management of large fleets of devices. About Robustel: Robustel are a Wireless IoT & WAN Edge solutions provider specialising in 5G, 4G/LTE & LPWAN devices, helping the enterprise in smart cities, transportation, smart water, energy and precision agriculture industry to deliver unbreakable connectivity by Robustel's hardware and cloud.

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