Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology

James Gillespie (), Tamíris Pacheco da Costa, Xavier Cama-Moncunill, Trevor Cadden, Joan Condell, Tom Cowderoy, Elaine Ramsey, Fionnuala Murphy, Marco Kull, Robert Gallagher and Ramakrishnan Ramanathan
Additional contact information
James Gillespie: School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry BT48 7JL, Northern Ireland, UK
Tamíris Pacheco da Costa: School of Biosystems & Food Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Xavier Cama-Moncunill: School of Biosystems & Food Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Trevor Cadden: Department of Management, Leadership & Marketing, Ulster University, Belfast BT15 1ED, Northern Ireland, UK
Joan Condell: School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry BT48 7JL, Northern Ireland, UK
Tom Cowderoy: Department of Management, Leadership & Marketing, Ulster University, Belfast BT15 1ED, Northern Ireland, UK
Elaine Ramsey: Department of Global Business and Enterprise, Ulster University, Londonderry BT48 7JL, Northern Ireland, UK
Fionnuala Murphy: School of Biosystems & Food Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Marco Kull: Whysor B.V., 5944 ND Arcen, The Netherlands
Robert Gallagher: Musgrave Northern Ireland, Belfast BT3 9HJ, Northern Ireland, UK
Ramakrishnan Ramanathan: Essex Business School, University of Essex, Southend-on-Sea, Essex SS1 1LW, UK

Sustainability, 2023, vol. 15, issue 3, 1-24

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.

Keywords: Internet of Things; IoT; food waste; cold chain; remote monitoring; sensor technology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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