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

Abstract

The development of the Internet of Things (IoTs) has empowered revolution in almost all walks of life. Although substantial effort has been made to bring IoT into manufacturing, there are still technical challenges to provide solutions of real-time pervasive multisensing, quality evaluation, and boundaryless information sharing, which put people at risk of deteriorated food products and food adulteration. In this article, we present an industrial IoT-based system for food product quality assessment and prediction. This research completes the real-time food quality assessment via radiofrequency identification (RFID) based multisensor 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 multidimensional information traceability and global data sharing. Machine-learning-based multisensor fusion is proposed to provide the 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.