Machine Learning-Enabled Internet of Things Solution for Smart Agriculture Operations

Abstract

Internet of things solutions with machine learning capabilities is a hot research area in industries, including agriculture. They can be used for data analysis and further forecasting the big data and intelligent applications in farming. In traditional farming, the main obstacles are disease prediction, automatic irrigation, energy harvesting, and constant monitoring. Today, farmers' cultivation of their crops has changed by introducing automated harvesters, drones, autonomous tractors, sowing, and weeding. Smart farming with ML-enabled IoT systems can improve crop harvesting decisions. The main topic of this chapter is to provide an ML-enabled IoT solution for smart agriculture. The MIoT solution in agriculture allows farmers to use predictive analytics to help them make better harvesting decisions. Designing a MIoT system for smart agriculture can assist farmers in improving yields, planning more effective irrigation, and making harvest forecasts by monitoring essential data like humidity, air temperature, and soil quality via remote sensors.