SMARTAGRI: An Intelligent Decision Support System for Smart Farming

Abstract

The most challenges facing sustainable development worldwide are the food shortage and the population growth. Therefore, recent technologies as artificial intelligence (AI), the Internet of Things (IoT), and the mobile internet offers many solutions to the challenges that are facing the world. Therefore, this work focuses on using the Artifical intelligence techniques to enhance smart farming practices.The intelligent system for smart farming presented in this paper utilizes case-based reasoning (CBR) to facilitate pest detection and management. The system aims to leverage historical data from past farming instances to inform decision-making in the present. The case base serves as a repository of past farming cases, storing information on environmental conditions, farming practices, pest occurrences, and corresponding solutions. The retrieval phase identifies the most similar cases, which provide insights into potential solutions or actions. The proposed intelligent system for smart farming, based on case-based reasoning, offers an effective approach to pest detection and management by leveraging historical farming experiences. By tapping into past knowledge, the system empowers farmers with valuable insights and informed decision-making, leading to optimized pest control strategies and improved agricultural outcomes.