AI in Managing Perishable Goods Inventory

Abstract

Managing perishable goods, such as food and medicine, is challenging due to their short shelf life and the need for high quality. Traditional methods often fail, leading to overstocking, stock-outs, and spoilage. This study explores how artificial intelligence (AI) can transform this field using machine learning, predictive analytics, and computer vision. AI improves demand forecasting by analysing data such as past sales and weather patterns. Predictive analytics uses real-time IoT sensor data to predict shelf life, while computer vision ensures quality monitoring. Case studies from Coles, Walmart, and Migros show AI's success in reducing waste, optimizing inventory, and boosting customer satisfaction. However, challenges include data integration, high costs, and employee training. Future trends suggest integrating AI with blockchain for better transparency and sustainability. AI can revolutionize perishable goods inventory management, making it more efficient, adaptable, and environmentally friendly.