可追溯性
计算机科学
信息共享
供应链
传感器融合
元数据
射频识别
产品(数学)
质量(理念)
智能传感器
系统工程
物联网
无线传感器网络
工程类
嵌入式系统
人工智能
计算机安全
计算机网络
万维网
软件工程
哲学
法学
几何学
认识论
数学
政治学
作者
Chenyang Song,Zhipeng Wu,J. M. N. T. Gray,Zhaozong Meng
标识
DOI:10.1109/tii.2023.3262197
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI