Machine Learning Based Approach to Reduce Food Wastage

Food wastage is a major issue that affects the economy, society, and environment on a global scale. Over one-third of the food produced worldwide is lost or wasted each year, underscoring the necessity for sustainable food systems. This research proposes an innovative solution that leverages technology to address food wastage reduction. An application is developed with a focus on four key categories: food wastage prediction and analysis, demand prediction and ingredient optimization, forecasting of near-expiry food prices, and accurate recycling method prediction. By incorporating machine learning and predictive modeling, the application provides restaurants and food administrators with comprehensive organizational statistics to effectively mitigate food wastage. The solution offers a data-driven approach to better plan events, reduce waste in the food industry, accurately forecast both demand and ingredient requirements, strategically focus on prices based on shelf life and predict optimal recycling methods. Through this multi-pronged approach, we aim to tackle the complex issue of food wastage and help to establish sustainable food systems.