Enhancing Agricultural Sustainability Through Robotic-IoT Systems for Real-Time Monitoring Soil Contamination

Soil degradation due to pollution and unsustainable agricultural practices threaten global ecosystems This paper introduces an advanced Internet of Things (IoT)-based robotic system designed to monitor soil quality and detect microplastic contamination in real-time. and the system Integrating portable sensors NIR spectroscopy provides efficient analysis of large soil sample volumes with minimal preparation, providing rapid and precise assessments that measure key soil, as well as AI analytics that provides accurate and scalable environmental data collection. This project uses machine learning algorithms, such as the Random Forest algorithm, to enable the system to achieve a 96% accuracy rate in microplastic detection and 91% accuracy in pollutant analysis. Providing reliable soil assessments plays an integral role in combatting environmental degradation, improving agricultural productivity, and encouraging sustainable land management practices.