Gillespie, James and da Costa, Tamíris Pacheco da and Cama-Moncunill, Xavier and Cadden, Trevor and Condell, Joan and Cowderoy, Tom and Ramsey, Elaine and Murphy, Fionnuala and Kull, Marco and Gallagher, Robert and Ramanathan, Ramakrishnan (2023) Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology. Sustainability, 15 (3). p. 2255. DOI https://doi.org/10.3390/su15032255
Gillespie, James and da Costa, Tamíris Pacheco da and Cama-Moncunill, Xavier and Cadden, Trevor and Condell, Joan and Cowderoy, Tom and Ramsey, Elaine and Murphy, Fionnuala and Kull, Marco and Gallagher, Robert and Ramanathan, Ramakrishnan (2023) Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology. Sustainability, 15 (3). p. 2255. DOI https://doi.org/10.3390/su15032255
Gillespie, James and da Costa, Tamíris Pacheco da and Cama-Moncunill, Xavier and Cadden, Trevor and Condell, Joan and Cowderoy, Tom and Ramsey, Elaine and Murphy, Fionnuala and Kull, Marco and Gallagher, Robert and Ramanathan, Ramakrishnan (2023) Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology. Sustainability, 15 (3). p. 2255. DOI https://doi.org/10.3390/su15032255
Abstract
There are approximately 88 million tonnes of food waste generated annually in the EU alone. Food spoilage during distribution accounts for some of this waste. To minimise this spoilage, it is of utmost importance to maintain the cold chain during the transportation of perishable foods such as meats, fruits, and vegetables. However, these products are often unfortunately wasted in large quantities when unpredictable failures occur in the refrigeration units of transport vehicles. This work proposes a real-time IoT anomaly detection system to detect equipment failures and provide decision support options to warehouse staff and delivery drivers, thus reducing potential food wastage. We developed a bespoke Internet of Things (IoT) solution for real-time product monitoring and alerting during cold chain transportation, which is based on the Digital Matter Eagle cellular data logger and two temperature probes. A visual dashboard was developed to allow logistics staff to perform monitoring, and business-defined temperature thresholds were used to develop a text and email decision support system, notifying relevant staff members if anomalies were detected. The IoT anomaly detection system was deployed with Musgrave Marketplace, Ireland’s largest grocery distributor, in three of their delivery vans operating in the greater Belfast area. Results show that the LTE-M cellular IoT system is power efficient and avoids sending false alerts due to the novel alerting system which was developed based on trip detection.
Item Type: | Article |
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Uncontrolled Keywords: | Internet of Things; IoT; food waste; cold chain; remote monitoring; sensor technology |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 01 Feb 2023 20:45 |
Last Modified: | 16 May 2024 21:41 |
URI: | http://repository.essex.ac.uk/id/eprint/34799 |
Available files
Filename: sustainability-15-02255.pdf
Licence: Creative Commons: Attribution 4.0