Combining Blockchain, IoT and AI for Food Safety Assurance: A Systemic Approach

Various issues are inherent in the traditional food supply chains that affect the quality and safety of the food items. These include contamination of food, fraudulent activities, inefficiencies, and lack of transparency. This research presents an integrated system to improve food safety management. The system implements blockchain to save the data safely, IoT to streamline real-time monitoring, and AI for predictive analysis. While previous research considered these individual components, the novelty of this study is its successful assembly into a single framework. The system reduces latency and improves decision-making across the supply chain by leveraging Convolutional Neural Networks (CNNs) and edge computing. When the system underwent a pilot study, it was able to demonstrate its potential for improving operational efficiency and reducing waste. The reaction time to food safety incidents decreased by 30%, and spoilage detection accuracy increased from 10-15% to 25%. In addition, this research demonstrates a theoretical framework for technology integration in supply chains and provides feasible methods to improve the food security level through the application of technologies and quality assurance. It created a performance benchmark for technological applications regarding food safety.