Cloud-based Decision Support Systems for Securing Farm-to-Table Traceability using IoT and KNN Algorithm

To maintain food safety and security today, tracking it from the farm to the table is crucial. A potential solution to this problem is to use Internet of Things (IoT) technology in conjunction with strong algorithms. To improve farm-to-table traceability, a cloud-based decision-support system that uses the K-Nearest Neighbors (KNN) algorithm in combination with the IoT infrastructure is proposed. At several points throughout the supply chain, the system incorporates IoT devices like RFID tags and sensors to gather and communicate data in real time. Important details like location, temperature, humidity, and handling procedures are included in this data. The cloud-based architecture provides a scalable and easily available platform for storing, processing, and analyzing the massive amounts of data created. The KNN algorithm examines the data and finds patterns or anomalies that might show possible dangers to food safety. This method is well-known for its simplicity and efficacy in classifying jobs. The system can assist stakeholders' decisions and give timely suggestions by combining real-time inputs with historical data. The proposed system is characterized by its reactivity, scalability, and openness. By building trust and accountability throughout the supply chain, stakeholders, including consumers, regulators, distributors, and farmers, may access essential information on the path of food items. Incorporating it with preexisting systems makes it possible to use machine learning to make incremental improvements.