Publication

Abstract : The world's population is predicted to grow by nearly 10 billion in the year 2050, which increases the food and agricultural demands. Hence, farmers worldwide are under continuous pressure to increase crop yield to satisfy the increasing food demand. To support the farmers in food production, crop monitoring and soil management are essential tasks. The traditional human observation-based crop and soil monitoring require more time and manpower. Hence, there is a need for smart crop and soil monitoring systems. This chapter is focused on different digital imaging-based Artificial Intelligence (AI) approaches such as machine learning, and deep learning that are used for smart crop and soil monitoring. There has been limited research work on the usage of smart intelligent techniques in crop and soil monitoring. This chapter attempts to identify the research gap in smart crops and soil monitoring. Future research trends would focus on integrating hybrid AI and reinforcement learning techniques for agricultural monitoring and management.