Agriculture drives India’s economic development, necessitating modern technologies to enhance productivity and sustainability for the growing population’s food demands. An Internet of Things (IoT)-based soil nutrient analysis and crop recommendation system for precision agriculture are present in this paper. Sensors measure soil properties like pH, color, humidity, and temperature interfaced using Arduino board. Real-time data is transmitted to the cloud via Wi-Fi. In the cloud, soil nutrient data undergoes preprocessing and analysis using the random forest machine learning (ML) algorithm. This provides personalized crop recommendations tailored to specific soil and environmental conditions. The real-time data is collected and analyzed that enables precise, informed decision-making for farmers to optimize resource utilization and enhance crop yields. Incorporating IoT in addition to machine learning (ML) allows data-driven decisions for better resource management and increased productivity. This innovation meets growing food demands through sustainable precision agriculture practices, contributing to India’s economic progress. The proposed prototype demonstrated 98% accuracy in providing recommendation of crop based on soil nutrient analysis.