Optimizing Cold Chain Systems: A Comprehensive Study on the Impact of Sensor-Based Environmental Monitoring

Published 30 June 2022 •  vol 3, no 1  • 


Authors:

 

Jose Arturo Garza-Reyes, University of Derby, UK

Abstract:

 

In light of the increasing number of food poisoning incidents, ensuring food delivery under optimal conditions is crucial for protecting consumer health. To tackle this pressing issue, many delivery companies are proactively launching pilot projects aimed at establishing an effective cold chain system. A cold chain is an integrated service that meticulously maintains the quality of agricultural products, meat, fruits, vegetables, beverages, and other groceries throughout transport and storage—from primary production sites to the end consumer. When food is subjected to temperatures beyond the recommended range, its quality deteriorates, leading to potential health risks. This highlights the urgent need for a comprehensive monitoring and control system that regularly assesses environmental conditions through the use of advanced sensors, such as those for temperature and humidity. In this paper, we introduce an innovative method for remotely monitoring the environmental status of delivery vehicles. Our approach employs state-of-the-art temperature and humidity sensors, alongside a ZigBee communication network and a mobile communication-equipped set-top box. This setup allows for real-time monitoring of conditions from remote locations. With our system in place, if temperature or humidity levels become inappropriate, immediate warning signals are dispatched to both the driver and the remote monitoring station, safeguarding food quality and ensuring optimal delivery conditions.

Keywords:

 

Food Poisoning Incidents, Cold Chain System, Health Risks, ZigBee

Citations:

 

APA:
Garza-Reyes, J. A. (2023). Optimizing Cold Chain Systems: A Comprehensive Study on the Impact of Sensor-Based Environmental Monitoring. Journal of Science and Engineering Management, 3(1), 13-22. https://doi.org/10.33832/jsem.2022.3.1.02