System Architectures for Sensor-Based Dynamic Remaining Shelf-life Prediction

Author:

Jevinger Åse1,Davidsson Paul1

Affiliation:

1. Malmö University, Malmö, Sweden

Abstract

Different storage and handling conditions in cold supply chains often cause variations in the remaining shelf life of perishable foods. In particular, the actual shelf life may differ from the expiration date printed on the primary package. Based on temperature sensors placed on or close to the food products, a remaining shelf-life prediction (RSLP) service can be developed, which estimates the remaining shelf life of individual products, in real-time. This type of service may lead to decreased food waste and is used for discovering supply chain inefficiencies and ensuring food quality. Depending on the system architecture, different service qualities can be obtained in terms of usability, accuracy, security, etc. This article presents a novel approach for how to identify and select the most suitable system architectures for RSLP services. The approach is illustrated by ranking different architectures for a RSLP service directed towards the supply chain managers. As a proof of concept, some of the most highly ranked architectures have been implemented and tested in food cold supply chains.

Publisher

IGI Global

Subject

Information Systems and Management,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems,Management Information Systems

Reference40 articles.

1. Quality Attributes.

2. Bartels, P.V., Tromp, S.O., Rijgersberg, H., & Kreft, F. (2010). Improvement of sustainability in the perishable food supply chain by using communicative packaging devices. In Towards Effective Food Chains: Models and Applications (pp. 275-291).

3. A Petri net based simulation approach for evaluating benefits of time temperature indicator and wireless technologies in perishable goods retail management.;N.Bhushan;The Second International Conference on Simulation and Modeling in the Food and Bio-Industry (FOODSIM’2002),2002

4. Bijwaard, D. J., van Kleunen, W. A., Havinga, P. J., Kleiboer, L., & Bijl, M. J. (2011). Industry: Using dynamic WSNs in smart logistics for fruits and pharmacy. In The 9th ACM Conference on Embedded Networked Sensor Systems.

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