Edge AI for Real-Time and Intelligent Agriculture

Abstract

Advancements of the last decade in edge computing, edge IoT, and edge artificial intelligence now allow for autonomous, efficient, and intelligent systems to be proposed for various industrial applications. Intelligence agricultural solutions allow farmers to achieve more with less while improving quality and providing a rapid go-to-market approach for produce. Using AI is an effective technique to detect any crop health concerns or nutrient inadequacies in the field. Plant diseases affect the food system, economy, and environment. This chapter covers intelligent agriculture & challenges in front of technology. It focuses AI application using machine learning, artificial neural network (ANN), and deep learning. The various AI applications in agriculture for land monitoring, crop and varietal selection, smart irrigation or automation of irrigation, monitoring of crop health, crop disease detection, predictive analytics, weed control, precision agriculture, harvesting, yield estimation and phenotyping, supply chain management, and food quality.