Proceedings Article | 21 December 2023
KEYWORDS: Data modeling, Transportation, Clouds, Environmental monitoring, Data transmission, Databases, Data storage, Design and modelling, Sensors, Internet of things
The cold chain logistics of oysters starts from the moment they are harvested and ends when they reach the consumers’ homes. The process includes various stages: pre-processing, packaging, pre-cooling, processing, cold storage, loading, transportation, and sales. Due to inadequate quality control in the logistics process, fresh oysters often experience a significant decline in quality during transportation and storage, resulting in substantial losses. To address this issue, this article presents a real-time, traceable, and visual quality monitoring system for oyster cold chain logistics. It combines RFID technology with the development of a unique binding technique for preservation boxes and utilizes a hybrid technology incorporating “RFID+4G+DTU+MQTT+cloud storage + Web” to enable real-time collection of oyster transportation environmental parameters and distributed, non-volatile, and cost-effective data storage. A supporting B-S mode system management platform was developed and deployed on a cloud server. The system, with the flow of information as its main focus, provides functions including personnel management, oyster identification and traceability, data visualization monitoring, and quality prediction. The online operation of this system has proven to be highly real-time and stable, effectively enhancing the quality monitoring capability throughout the entire oyster transportation process, and it has demonstrated significant economic and social benefits.
