Our research introduces an AI-powered food freshness monitoring system that integrates low-cost, thin-film sensors into smart packaging. These sensors continuously track key freshness indicators such as gas composition, humidity, and temperature, transmitting real-time data to processing plants for AI-driven analysis and predictive evaluation. By leveraging edge computing, IoT connectivity, and machine learning algorithms, the system enables automated quality assessment, early spoilage detection, and optimized supply chain decisions, reducing food waste and ensuring consumer safety. This cost-effective, scalable solution transforms food monitoring, enhancing transparency, efficiency, and sustainability in the agriculture and food industries.