Authors - Om Gadhvi, Srushti Pawar, Shravan Gadhvi, Mansi Jadhav, Manya Gidwani Abstract - Farmers in Maharashtra, India face substantial costs and low utilization rates on equipment, leading to significant financial strain. We suggest implementing an AI-powered Dynamic Machine Price Prediction Model that we can use for a digital platform that enables renting out equipment. This model uses Linear Regression, Random Forest, and Gradient Boosting to output what prices equipment should sell for, given the age, how often farmers use it, when they use it, and market demand. Gradient Boosting turned out to be the most accurate model in our exams, giving us a 94% R² score so that our model predictions are trustworthy. The website is built using the MERN stack, and it employs secure transactions through PayPal and a feature that enables farmers to search for equipment based on their location. By adjusting equipment prices on the go, we provide insights to farmers into how much they should charge for renting out their equipment in all conditions The proposed system enhances resource utilization, sustainability, and economic resilience in the agricultural sector.
