Publication

Abstract : In this chapter, an elaborated description of machine learning (ML)-based IoT system for smart and sustainable agriculture in modern perspective is presented. Idea for future perspective to advanced ML-IoT system development is emphasized, and a CNN and LightGBM-based crop recommendation system is suggested. Internet of things (IoT) is an emerging technology and dedicated platform to connect the remote systems to each other. Recently, IoT is widely adopted in smart and sustainable agriculture for environmental and crop data acquisition. The sensors data collected from IoT devices is analyzed using ML techniques for detection and further action is taken for improvement in farming. The ML-IoT solution assists farmers in deciding which state of action to be taken as per the analysis of IoT sensor devices data such as temperature, light intensity, humidity, ultraviolet range, and soil moisture and boost agriculture for sustainable goals. A comprehensive discussion is given of the present situation, applications, opportunities for study, constraints, and future issues.