Use of Machine Learning and IoT in Agriculture

In recent years, the agricultural sector has come under tremendous pressure due to the very high growth of the population. The need for food increased at a quadratic rate, and even the Food and Agriculture Organization (FAO) of the United Nations estimated that food production would have to grow by 70% worldwide to meet the global food demand. Due to limited arable lands and countful availability of renewable resources, there is a need to increase the agricultural yield even more seriously. Agriculture is affected significantly by recent technological advancements in the domains of Internet of Things (IoT), Machine Learning (ML), and deep learning (DL). Researchers are helping farmers by applying these technologies to precisely automate crop cultivation methods, management, and production. This chapter provides the latest insights into the latest research initiatives that significantly impact smart agriculture and farming. It provides a detailed impact of IoT, machine learning, and data analytics that can be used for disease control; monitoring the climate; measuring soil temperature, nutrient value, and moisture levels; controlling and analyzing water consumption; and much more. These shall help follow scientific procedures for plant growth and increase crop yield. It refers to the latest work of researchers to provide solutions to various agricultural challenges, using several ways to automate and maximize agricultural produce.