A DATA-DRIVEN BIG DATA AND IOT APPROACH FOR FOOD SAFETY TRACEABILITY

Abstract

This project examines the feasibility of enhancing food safety traceability and monitoring systems throughout the entire food supply chain by utilising Big Data and Internet of Things (IoT) technologies. The proposed system utilises IoT-enabled sensors, RFID identifiers, wireless communication, and cloud-based platforms to gather real-time data on food production, storage, transportation, and distribution. In order to monitor environmental conditions, identify contamination hazards, and ensure conformance with product quality and safety laws, big data analytics techniques are employed to manage and analyse vast quantities of heterogeneous data. By enabling the continuous monitoring and rapid identification of hazardous compounds, the integration of these technologies enhances transparency, traceability, and decision-making. Additionally, the implementation of contemporary predictive analytics and monitoring systems results in diminished food waste, a decrease in the incidence of foodborne illnesses, and an increase in consumer confidence. The research emphasises the necessity of integrating IoT and Big Data to develop intelligent, dependable, and effective food safety management systems for the contemporary agriculture and food industries.