DEVELOPMENT OF AI-DRIVEN PREDICTIVE MODELS AND IOT-BASED SOLUTIONS FOR ENHANCING FOOD QUALITY AND SAFETY IN SUPPLY CHAINS

Abstract

The global food supply chain is under pressure to address critical issues such as maintaining food quality, ensuring safety, and reducing waste. This paper delves into the transformative role of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in improving food quality and safety throughout supply chains. AI-powered predictive models, leveraging machine learning algorithms, are employed to evaluate food shelf life and enhance operational efficiency. Meanwhile, IoT-based innovations, such as cost-effective sensors and real-time monitoring systems, contribute to traceability and adherence to quality standards. The integration of blockchain technology for secure data handling is also explored, offering greater transparency and traceability. Through case studies and proof-of-concept applications, the paper highlights the practical use and advantages of these technologies in real-world contexts. The discussion concludes by addressing challenges, such as costs, the need for technical expertise, and regulatory compliance, while pointing toward future research opportunities to foster sustainable and resilient food supply chains.