Tobacco Waste Management System Using ML

Tobacco production generates large amounts of waste material including stalks and leaves and stems that industries typically dispose using destructive methods of fires or trash dumps. This work demonstrates a Machine LearningBased Tobacco Waste Management System (ML-TWMS) utilizing tobacco stems to produce electrical energy. Through Random Forest Regression (RFR) the system calculates predicted energy outputs from essential characteristics including moisture content and calorific value alongside chemical composition. Real-world data was used for training the model which underwent optimization through Grid Search CV and received feature scaling optimization to boost prediction precision. ML-TWMS utilizes data analytics to create energy from waste transformation together with sustainable principles and circular economy methods and renewable energy solutions in tobacco production systems.