the internet of things are reallty things not people

IoT Security

Article | June 27, 2023

Every major industry, including retail, transportation, banking, healthcare, and energy, has significantly benefited from the Internet of Things. Processes like supply chains are where the Internet of Things best demonstrates its promise. Applications for management, forecasting, and oversight aid fleet managers in increasing distribution's operational effectiveness and decision-making openness. Some of the primary goals for IoT deployment in supply chain management include tracking and monitoring. For example, warehouse and fleet managers can use technology to keep an eye on their stock and freight. Reasons to Use IoT in Supply Chain Management Real-time Location-tracking Thanks to the Internet of Things, managers have access to a consistent stream of real-time data on the product's location and the environment surrounding transportation. You may keep track of the delivery of both finished items and raw materials, and you will be informed if the product is transported in the wrong direction. Monitoring of Storage Conditions Environmental sensors allow management to monitor cargo conditions and take immediate action when something changes. One of the most popular IoT supply chain systems, for example, collects data on pressure, humidity, the temperature inside vehicles, and other factors that could harm the goods and then automatically adjusts the environment. Enhance Your Emergency Planning Supply chain managers can design routes with the use of IoT and data analytics, taking into account traffic, weather, potential accidents, and other delay-causing events that may occur along the way. The Internet of Things collects all the data required to create adaptable backup plans and identify the source of any current delays. Also, supply chain managers can get alerts from the system in real time, which speeds up reducing risks. Forecast Goods Arrival and Movement IoT devices and data analytics systems are used by managers to enhance the decision-making process and boost the accuracy of delivery estimates. Real-time tracking lets businesses keep track of products as they are shipped, predict when they will arrive, and plan for and reduce the risk of delays. Conclusion There are many different IoT applications for supply chain management. For example, it improves communication between parties, makes it easier to track and monitor commodities, and makes planning more precise. As long as you have a clear goal for what you need the technology to achieve for you, an IoT-based platform is an excellent investment for both small and large organizations. It's also essential to bring on a talented team for the design and development phase.

IoT Security

Article | July 17, 2023

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. For businesses offering AI-enabled solutions, similar advancements can be achieved with pipeline automation too. That includes significant cuts in annotation and QA time. By leveraging SuperAnnotate’s platform, hundreds of companies recorded faster task completion and more accuracy in prediction results. 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. Join hundreds of leading companies who build super high-quality training data up to 5x faster using SuperAnnotate’s intuitive data curation and robust project management features. 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.

Enterprise Iot

Article | July 20, 2023

Explore the world of readings on IoT security, to address complex cyber security challenges and privacy issues. It caters to a wide range of readers including industrialists, students & enthusiasts. The Internet of Things (IoT) has revolutionized industries, enabling innovative applications and improved efficiency. However, along with the numerous benefits of the IoT comes the pressing need for robust security measures. As IoT devices become more prevalent and interconnected, their risks and vulnerabilities also increase. The experts in the domain must stay updated with the latest security practices and techniques to ensure IoT systems' integrity, confidentiality, and availability. A wide range of books has been explicitly tailored address these security concerns. 1. Analytics for the Internet of Things (IoT) Author: Andrew Minteer Analytics for the Internet of Things (IoT): Intelligent analytics for your intelligent devices provides a comprehensive guide for businesses aiming to make informed decisions and gain greater control over their IoT infrastructure. Written by an expert in the field, this book equips readers with the essential knowledge and techniques to solve the unique challenges associated with IoT and extract valuable insights from vast amounts of data. The book begins by tackling the complex task of extracting value from large volumes of often complex IoT data, empowering readers to make data-driven decisions. Strategies to address data quality concerns are discussed, ensuring that readers are equipped to handle the inherent challenges. It offers readers approaches to optimize business value and bring down costs. Scaling both data storage and analytics is a critical consideration in IoT deployments, and the book provides practical insights into handling scale effectively. The book covers a range of topics, including transmission protocols, data flow, value extraction, geospatial analytics, machine learning, and optimizing business value. 2. Industrial Internet of Things (IIoT) Editors: R. Anandan, Suseendran Gopalakrishnan, Souvik Pal, Noor Zaman One of the essential IoT security books, Industrial Internet of Things (IIoT): Intelligent Analytics for Predictive Maintenance comprehensively explores how the industrial internet is transforming through increased network agility and the ability to deploy, automate, integrate artificial intelligence, orchestrate, and secure diverse use cases at hyperscale. The adoption of industrial automation on a large scale is revolutionizing business processes, with the market for industrial robots projected to reach $73.5 billion by 2023. The book highlights how IoT industrial automation provides numerous advantages, including enhanced efficiency, high accuracy, cost-effectiveness among others. This book presents real-world case studies in IIoT, robotic and intelligent systems, and web-based applications. The content is tailored to appeal to a broad audience, including working professionals, educators, and researchers in various technical disciplines. The book provides industry leaders with valuable insights by proposing business models that revitalize the workforce. 3. IoT and OT Security Handbook Authors: Smita Jain, Vasantha Lakshmi, Foreword: Dr Rohini Srivathsa IoT and OT Security Handbook: Assess risks, manage vulnerabilities, and monitor threats with Microsoft Defender for IoT is a comprehensive guide that equips industrial security, IoT security, and IT security professionals with the knowledge and tools to effectively address cybersecurity challenges in the rapidly evolving world of IoT and OT. In the era of the Fourth Industrial Revolution, where digital transformation and connected industries dominate, the book sheds light on the pressing security concerns that must be addressed to ensure data protection and operational resilience. Through a deep dive into the Purdue model of reference architecture, readers gain a solid understanding of common cyber-attacks prevalent in IoT and OT environments. The centerpiece of the book revolves around Microsoft Defender for IoT, a powerful security solution specifically designed to safeguard IoT and OT ecosystems. Furthermore, the concept of zero trust, which is crucial for establishing a robust security foundation, is thoroughly explored with practical insights on its implementation in the context of IoT devices. 4. Practical Internet of Things Security Author: Brian Russell, Drew Van Duren Practical Internet of Things Security: Design a security framework for an Internet connected ecosystem is an indispensable guide that navigates the complex realm of securely building and deploying systems in our IoT-connected world. The book primarily targets IT security professionals, security engineers, and individuals responsible for ensuring the security of their organization's data in the IoT landscape. However, it also serves as a valuable resource for business analysts and managers seeking to understand and address the security challenges associated with IoT deployments. Readers will gain a wealth of knowledge and practical skills, including breaking down cross-industry barriers, building a rock-solid security program, applying systems security engineering and privacy-by-design principles, and harnessing cloud-based systems. It delves into the unique security challenges associated with IoT and provides practical guidelines for architecting and deploying a secure IoT ecosystem within an enterprise. 5. IoT: Security and Privacy Paradigm (Internet of Everything (IoE)) Editors: Souvik Pal, Vicente García Díaz, Dac-Nhuong Le IoT: Security and Privacy Paradigm is a comprehensive and authoritative resource that explores the evolution of security and privacy issues within the realm of the IoT. This book serves as a single reference point for students, researchers, and practitioners seeking to better understand the IoT security platforms and privacy landscape. The book adopts security engineering and privacy-by-design principles to design and implement robust cyber-security solutions within IoT ecosystems. It takes readers on a journey, starting with exploring security issues in IoT-enabled technologies and their practical applications. The book provides practical guidance on tackling security challenges and constructing a secure infrastructure for IoT devices. The book thoroughly discusses security challenges and solutions in areas such as RFID, WSNs, and IoT. The primary audience for this book includes specialists, researchers, graduate students, designers, experts, and engineers focused on security-related issues and research. 6. IoT Security Issues Author: Alasdair Gilchrist IoT Security Issues addresses the rapid proliferation of internet-connected devices, where security often takes a backseat to product development. This book delves into the inherent vulnerabilities and IoT security challenges, offering insights on how to address and mitigate these issues. By examining the root causes of these problems and emphasizing the importance of programming and security best practices, the author presents practical solutions to combat the lax security processes prevalent in the IoT landscape. This book caters to a wide range of readers, including programmers who have yet to focus on the IoT, security professionals, and individuals with a keen interest in hacking and making. While a basic programming background would be beneficial for certain chapters later in the book, the core content is explained in a manner that is approachable for readers from various backgrounds. 7. Security and Privacy Issues in IoT Devices and Sensor Networks Editors: Sudhir Kumar Sharma, Bharat Bhushan, Narayan C. Debnath This book, of all the IoT security books, delves into the critical aspects of security breaches in IoT and sensor networks, offering a comprehensive exploration of potential solutions. The book takes a two-fold approach, thoroughly examining the fundamentals and theoretical foundations of sensor networks and IoT security. It then explores the practical IoT security solutions that can be implemented to enhance the security of these elements, providing illuminating case studies to reinforce understanding. The book is an invaluable resource for industry professionals working with wireless sensor networks (WSN) and IoT systems, enabling them to elevate the security of these interconnected systems. Additionally, researchers, material developers, and technology specialists grappling with the intricate nuances of data privacy and security enhancement will find the book's comprehensive information highly beneficial. Final thoughts IoT security for professionals involves implementing secure communication protocols, strong authentication, device management, data encryption, access control, and regular security audits. It is crucial to stay updated, maintain a security-aware culture, and prioritize the ongoing monitoring and adaptation of security measures to address emerging threats. The above listed books delve into various aspects of IoT security, providing insights, strategies, and practical solutions to mitigate risks and protect IoT ecosystems. This article highlights some essential IoT security books that are indispensable resources for IoT professionals striving to enhance the security posture of their organizations. They also provide real world case studies, best practices and strategies to minimize risks.

Article | January 29, 2021

We live in the age of technological advancement and progress is happening at an unprecedented speed. With newer technologies emerging every day, it is unreasonable to not be intrigued by their implications on business. Artificial Intelligence and the Internet of Things are two independent technologies that are changing the face of several industries, one advancement at a time. While Artificial Intelligence promises to automate and simplify everyday tasks for humans, the Internet of Things is rapidly bridging the gap between physical and digital. The convergence of these two technologies promises to simplify lives through connected devices. This convergence has already been witnessed in several industries and is being hailed as the Artificial Intelligence of Things or AIoT. Experts across industries claim that Artificial Intelligence of Things is set to redefine the future of the industry and mold intelligent and connected systems. Applications The Artificial Intelligence of Things is a congruence of AI and IoT infrastructures being used to achieve several applications across industries more accurately and efficiently. We already know that IoT generates scores of data, but this data is pretty useless in its raw form, it the organization, analysis, and interpretation of the data that makes it invaluable. Manually parsing through all of that data can take months given the sheer volume of it. This is where AI comes in. Modern AIs are programmed to efficiently handle large amounts of data to turn them into coherent pieces of information. Together, IoT and AI make for a great technological tool for business. Take a look at some other applications of AIoT in business. Marketing Good marketing comes from a series of well informed and well-researched decisions. For example, deciding on where the budget is allotted, what market strategy is put into action, or which campaign is prioritized. While human decisions can be fallible, most businesses today cannot afford to make big mistakes. This is where AIoT turns into a big help. Through the Artificial Internet of Things, marketers can get reports about market trends, probabilities, customer behavior, and more, most of these in real-time. These reports help marketers make informed decisions that are much likely to result in success. Drones Drones are one of the biggest advancements of IoT technology. In fact, drones are so popular with such varied applications, that drones can be talked of as a separate technology in themselves. These flying machines were originally invented for military purposes such as surveillance or weapon deployment but markets have rapidly found utility in drones for many other purposes. Today, they are being used as delivery bots, nature conservation, surveillance mechanisms, research tools, safety equipment, field substitutes, agriculture, geo-mapping, and a lot more. With AIoT, drones have become smarter, more adaptable, and way more useful. As Artificial intelligence allows drones to make minor decisions, their applications have gotten wider and more sophisticated. In a brilliant use case of AIoT, a drone enthusiast named Peter Kohler has started the Plastic Tide Project which uses drones to locate plastic on the ocean surfaces. The drones are powered by AI which allows them to locate plastic and not other elements like marine life or corals. These drones then hover over the plastic waste and speed up the ocean cleaning process. Drones can be used to map farmlands, determine the optimum farming processes and schedules, count the cattle, monitor their health, and even undergo certain physical tasks in agriculture, all thanks to the Artificial Intelligence of Things. AR/VR Augmented Reality and Virtual Reality are both heavily data-dependent technologies. There cannot be a convincing virtual reality unless there is data available for creating the said simulation. AR and VR have both found applications in several industries like healthcare, gaming, training, education, design, and manufacturing. Most of these applications fall in the critically important category and therefore, the AR or VR must be accurate to the minutest detail. This can only be achieved with mounds of data from the actual reality. With the help of IoT, this data is not accessible, and AI interprets it in a way that it can be turned into several different formats. Infrastructure One of the most useful applications of AIoT has been infrastructure. Artificial Intelligence of Things has fuelled innovation and planning for smart cities across the world. With the open data available for urban planning, cities are now becoming safer and more convenient to live in. AIoT has also made it possible to optimize energy consumption and ensure safer roadways through traffic surveillance. With smart energy grids, smart streetlights, and smart public transport, energy consumption and carbon emissions are both controlled. Moreover, AIoT has given a whole new life to urban design, and now comfort and aesthetics do not have to be sacrificed for convenience. Energy As we discussed above, Artificial Intelligence of Things is instrumental in optimizing energy consumption in urban areas. However, the applications of AIoT in the energy sector are not limited to smart cities. Many utilities providers across the globe are already gearing up to incorporate AIoT in their process. The expected benefits from the Artificial Intelligence of Things range from improved grid management, power quality, reliability, and restoration resilience to enhanced cybersecurity and better integration of distributed energy. Most utilities providers have still not adopted the new technology but with the increasing complexity of grid management and higher customer experience demands, there is no denying that they will have to deploy AIoT solutions to tackle these. Robotics In layman’s experience robots are either extremely sophisticated machines from sci-fi that undertake every task humans can and more, or they are these clunky things that can pass you the butter. In practice, however, robotics is a lot more practical than these ideas. Today, robotics is at the forefront of AIoT applications. The Artificial Intelligence of Things is being used in robotics for several applications such as surgical procedures, manufacturing, and even first aid. In healthcare specifically, AIoT powered robots are taking huge leaps. Robotic surgery eliminates the chance of human error and offers a much more precise surgical experience with minimum invasion. This enhances the success rate of surgery and aids faster recovery in patients. Logistics The convergence of AI and IoT has made a huge impact on logistics as it is now possible to automate the entire process, track the goods, as well as monitor the entire trajectory from deployment to delivery. With the addition of drones and robotics, even the last mile delivery can be automated with zero human intervention. This makes for faster delivery, better customer experience, as well as a well-designed supply chain management system. Industrial As the concept of adding smart sensors to physical objects emerged in the 1980s, a new term was coined a decade later—Industrial Internet of Things. IIoT is now a huge phenomenon of automating and optimizing industrial operation technologies across the globe. As IIoT is deployed in several factions of the industry including manufacturing, supply chain management, human resources, and energy management, these devices and sensors generate a massive amount of data daily. The data generated from even a single process can be dizzying, and this is where AI makes a difference. AI can not only manage this data but also find the relevant points of data and analyze it for business purposes. Edge Computing Artificial Intelligence has given way for another technology i.e. Edge computing. Edge computing allows a device to process data itself rather than rely on remote data servers to do so. It may seem like a small feat but think of the possibilities it offers—drones don’t have to be connected to find their way, smart appliances can interact with each other without a shared network, and thermostats can change the temperature based on your past preferences automatically. Edge computing is by no way a new technology but, in the future, it offers huge possibilities like smart automobiles and aircraft, or even robots in every home. Frequently Asked Questions What are the examples of Artificial Intelligence? Some of the most common examples of Artificial Intelligence are Google Maps and Uber. The AI allows you to find routes to any destination and even hail rides there. How does AI help IoT? Artificial Intelligence can comb through millions of data points in seconds to come up with patterns and analyze them. As IoT generates a lot of data continuously, AI is a powerful and complementary technology that helps IoT. Is IoT related to Artificial Intelligence? Internet of Things and Artificial Intelligence are two separate technologies that interact with each other well as their functions aid each other progress. 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