An RFID-Powered Multisensing Fusion Industrial IoT System for Food Quality Assessment and Sensing

Abstract

The development in Internet of Things (IoT) have empowered revolution in almost all walks of life. Although substantial effort has been made to bring IoT in manufacturing, there is still technical challenges of providing solutions of real-time pervasive multi-sensing, quality evaluation and boundary-less information sharing, which put people at risk from deteriorated food products and food adulteration. This investigation presents an Industrial IoT-based system for food product quality assessment and prediction. This research completes the real-time food quality assessment via radio frequency identification-based multi-sensor fusion for the first time. Also, a novel concept of shelf-life prediction is proposed. The RFID-powered sensors provide a new idea for nondestructive food product and environment sensing. A five-layer architecture considering sensing, controlling, communication, interfaces, and data analysis is highlighted. A novel RFID metadata structure is first proposed to achieve multi-dimensional information traceability and global data sharing. Machine learning-based multi-sensor fusion is proposed to provide accurate quality assessment and prediction. The proposed system is implemented as a smart shelf system to demonstrate its feasibility and advantages. The system is of great significance in improving food safety, reducing food waste and providing powerful information support for food manufacturing line and supply chain management.