Machine Learning Modelling-Powered IoT Systems for Smart Applications

With the rapid development of Internet of Things (IoT) and the use of smart devices and social networks in our daily lives, applications-based on IoT are growing exponentially in many fields such industries, business and daily life activities. The IoT technology brings a lot of promise for humanity by improving life quality and comfort and by strengthening human bonds, among others. In the next few years, billions of connected devices will be spread across smart homes, vehicles, cities, and industries. Such connected devices, with restricted resources, will interchange with users and the surrounding environment. In this context, Machine Learning (ML), Which is able to provide embedded intelligence in the IoT devices and networks, can be leveraged to decode the meaning and behavior behind the device’s data, implement accurate predictions, and make decisions for several tasks. In this chapter, we present an overview of research works about ML-base IoT systems in different areas of applications. First, we present a deep overview of IoT’s technology. Then, we highlight the most fundamental concepts of ML categories and algorithms. After that, we shed light on the ML-based IoT critical challenges and provide some potential future research directions. Eventually, we present an IoT-based ML technique scenario for smart irrigation in Agriculture 4.0.