Automated Tuber Crop Harvesting Using IOT and Intelligent Yield Prediction for Precision Farming

Agriculture, as the backbone of the nation, is undergoing a transformational journey with the integration of technology, especially the Internet of Things. This research paper presents an innovative concept aimed at increasing tuber production by implementing an IoT-controlled tuber harvesting robot. Using an ESP32 camera for live video streaming and an Arduino for user control, the robot optimizes harvesting operations with precision. A mass estimator is seamlessly integrated with the force meter, providing calculated data and comparing it to predicted masses via sunspot numbers. By incorporating solar forecasts through polynomial regression and the decision tree, it captures 73.9% and 69.9% of the variation in yam and cassava yields, respectively. Rigorous accuracy testing, conducted in line with minimum solar activity in 2023 and 2024, confirms the reliability of the system, yielding impressive accuracy scores of 0.92 for yam and 0.87 for cassava. This research paper presents a new approach to revolutionize agricultural practices, showing the vital role of technological innovation in the development of the agricultural sector and subsequently contributing to the progress of the nation.