IoT-based intelligent crop rotation and recommendation system

Abstract

Traditional farming practices often rely on manual monitoring and crop selection, leading to inefficient use of resources and limited crop diversification. This study addresses these issues through the development of an IoT-based intelligent crop rotation and recommendation system that automates crop monitoring, irrigation, and crop selection processes. The system integrates DHT11 and NPK sensors to measure temperature, humidity, soil moisture, and nutrient levels (N, P, K), with real-time data displayed on a web-based application interface. An automated irrigation and fertilizer subsystem with SMS notifications enhances user control and remote accessibility. A crop recommendation module using the Euclidean Distance algorithm analyzes soil-nutrient data to identify the most suitable crops for the next planting cycle. System evaluation based on the ISO/IEC 25010 software quality model indicated high functionality, usability, reliability, portability, and maintainability, with an overall weighted mean of 3.958 (Agree) and a cronbach’s alpha of 0.9585, signifying excellent reliability. The system demonstrates the potential of internet of things (IoT)- based technologies in promoting crop diversification, optimizing farm productivity, and advancing sustainable agricultural practices.