Internet of Things

Companies have shifted primarily as a consequence of the rise of the Internet of Things (IoT), which makes it possible for electronic devices, including physical objects, to collaborate effortlessly and support real-time data processing, accumulation, and decision-making. By enabling highly intelligent, information-driven choices, the Worldwide Web of Things (WoT) and the use of machine learning (ML) have completely reshaped many enterprises. Using connected gadgets, the IoT creates tremendous amounts of information, which artificial intelligence (AI) examines to gain insights, determine consequences, and automate its activities. The IoT and ML integration improve system adaptation, improve immediate analytics, and enhance performance. The fundamental concepts, construction, conceptual models, software, and obstacles concerning IoT–ML connectivity will be addressed in the next section. The subject matter here addresses the basis of the IoT, including everything encompassing the framework, crucial items, and communication methods. All the challenges arising from the IoT have been solved, namely connectivity problems, weaknesses in security, resource limitations, and growing problems. This book chapter investigates and emphasizes the advantages of IoT–ML connectivity and decision-making through data-driven insights and discusses some case studies of automation in industries and it highlights the numerous advantages of the integration of the IoT and ML activity, such as improved effectiveness in processing large amounts of data and discusses about the different case studies and latest technologies and different challenges.