An integrated IoT Architecture to Monitor Food Quality along the Supply Chain
DOI:
https://doi.org/10.21048/IJND.2023.60.1.29955Keywords:
Supply chain management, nutrients, cold chain, internet of things, cloud, securityAbstract
Drop in nutrition value during food logistics impacts the health of consumers. Vegetables, fruits, fish, milk lose nutrients during logistics if it is not properly monitored. Real-time tracking and monitoring, large data handling and secure business transactions are key to the effective operation of supply chains. The COVID-19 pandemic has taught us the need for handling unforeseen situations in various sectors. Limitations to logistic operations, inaccessible warehouses, shutdown of consumer outlets for an unexpected duration, have affected the supply chain drastically. This has laid emphasis on the need for technology-based solutions that can monitor, control and make quick decisions, that can reduce losses. With this scenario as a background, a system architecture has been proposed to detect the nutrient value of food by periodically monitoring temperature and humidity in real-time and alerting the cold chain entities in cold chain environments. This architecture is proposed as an integration of Internet of Things (IoT) with cloud-based storage, to provide real-time data collection at the end-user, seamless storage and computation in the cloud and secure transactions at the business layer. An experimental setup of the system architecture has been configured and the implementation has been tested at a preliminary level. The performance of the application is analyzed and the proposed web application is efficient for large scale supply chain applications, provided scaling of hardware resources.
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Accepted 2022-11-24
Published 2023-03-01
References
Richey, R.G., Roath, A.S., Adams, F.G. and Wieland, A. A responsiveness view of logistics and supply chain management. J. Business Logistics, 2022, 43, 62-91. DOI: https://doi.org/10.1111/jbl.12290
Birkel, H. and Müller, J.M. Potentials of industry 4.0 for supply chain management within the triple bottom line of sustainability–A systematic literature review. J. Cleaner Produc., 2021, 289, 125612. DOI: https://doi.org/10.1016/j.jclepro.2020.125612
Amiri, S., Moghanjougi, Z.M., Bari, M.R. and Khaneghah, A.M. Natural protective agents and their applications as bio-preservatives in the food industry: An overview of current and future applications. Italian J. Fd. Sci., 2021, 33, 55-68. DOI: https://doi.org/10.15586/ijfs.v33iSP1.2045
Bibi, F., Guillaume, C., Gontard, N. and Sorli, B. A review: RFID technology having sensing aptitudes for food industry and their contribution to tracking and monitoring of food products. Trends in Food Science and Technology, 2017, 62, 91-103. DOI: https://doi.org/10.1016/j.tifs.2017.01.013
Ahmed, M., Rahaman, M.O., Rahman, M. and Kashem, M.A. (2019, December). Analyzing the Quality of Water and Predicting the Suitability for Fish Farming based on IoT in the Context of Bangladesh. In 2019 International Conference on Sustainable Technologies for Industry 4.0 2019, 1-5, IEEE. DOI: https://doi.org/10.1109/STI47673.2019.9068050
Mercier, S., Villeneuve, S., Mondor, M. and Uysal, I. Time-temperature management along the food cold chain: A review of recent developments. Comprehensive Reviews in Food Science and Food Safety, 2017, 16, 647-667. DOI: https://doi.org/10.1111/1541-4337.12269
Pebdeni, A.B., Roshani, A., Mirsadoughi, E., Behzadifar, S. and Hosseini, M. Recent advances in optical biosensors for specific detection of E. coli bacteria in food and water. Fd. Control, 2022, 108822. DOI: https://doi.org/10.1016/j.foodcont.2022.108822
Singh, J. and Singh, S.P. Damage reduction to food products during transportation and handling. In Handbook of Farm, Dairy and Food Machinery Engineering Academic Press. 2019, 741-770. DOI: https://doi.org/10.1016/B978-0-12-814803-7.00028-2
Li, L., Pegg, R.B., Eitenmiller, R.R., Chun, J.Y. and Kerrihard, A.L. Selected nutrient analyses of fresh, fresh-stored, and frozen fruits and vegetables. J. Fd. Compos. Analy., 2017, 59, 8-17. DOI: https://doi.org/10.1016/j.jfca.2017.02.002
Rahman, L.F., Alam, L., Marufuzzaman, M. and Sumaila, U.R. Traceability of sustainability and safety in fishery supply chain management systems using radio frequency identification technology. Fds, 2021, 10, 2265. DOI: https://doi.org/10.3390/foods10102265
Priyaa, P. K., Sathyapriya, S. and Arockiam, L. Nutrition monitoring and calorie estimation using internet of things (IoT). Int. J. Innov. Technol. Explor. Eng., 2019, 8, 2669-2672. DOI: https://doi.org/10.35940/ijitee.K2072.0981119
Gurtu, A. and Johny, J. Supply chain risk management: Literature review. Risks, 2021, 9, 16. DOI: https://doi.org/10.3390/risks9010016
Zhang, Y., Zhao, L. and Qian, C. Modeling of an IoT-enabled supply chain for perishable food with two-echelon supply hubs. Industrial Management and Data Systems, 2017. DOI: https://doi.org/10.1108/IMDS-10-2016-0456
Ashok, A., Brison, M. and LeTallec, Y. Improving cold chain systems: Challenges and solutions. Vaccine, 2017, 35, 2217-2223. DOI: https://doi.org/10.1016/j.vaccine.2016.08.045
Vrat, P., Gupta, R., Bhatnagar, A., Pathak, D.K. and Fulzele, V. Literature review analytics (LRA) on sustainable cold-chain for perishable food products: research trends and future directions. Opsearch, 2018, 55, 601-627. DOI: https://doi.org/10.1007/s12597-018-0338-9
Aziz, M.A., Ragheb, M.A., Ragab, A.A. and El Mokadem, M. The impact of enterprise resource planning on supply chain management practices. The Business and Management Review, 2018, 9, 56-69.
Haulder, N., Kumar, A., and Shiwakoti, N. An analysis of core functions offered by software packages aimed at the supply chain management software market. Computers and Industrial Engineering, 2019, 138, 106116. DOI: https://doi.org/10.1016/j.cie.2019.106116
LakshmiPriya, T.K.S. and Alagusundari, N. Smart Printed Paperboard for Green Infrastructure. In Emerging Technologies for Agriculture and Environment. Springer, Singapore. 2020, 2020. DOI: https://doi.org/10.1007/978-981-13-7968-0_18
James, D. and Lakshmi Priya, T.K.S. Improving the product services using IoT for controlling in-transit parameters. Our Heritage, 2020, 68, 376-382.
James, D. and Lakshmi Priya, T.K.S. An IoT-Based Traceability Framework for Small-Scale Farms. In Emerging Technologies in Data Mining and Information Security (pp. 841-851). Springer, Singapore. 2021. DOI: https://doi.org/10.1007/978-981-15-9927-9_81
, Rejeb, A., Keogh, J.G. and Treiblmaier, H. Leveraging the internet of things and blockchain technology in supply chain management. Future Internet, 2019, 11, 161. DOI: https://doi.org/10.3390/fi11070161
Litke, A., Anagnostopoulos, D. and Varvarigou, T. Blockchains for supply chain management: Architectural elements and challenges towards a global scale deployment. Logistics, 2019, 3, 5. DOI: https://doi.org/10.3390/logistics3010005
James, D. and Lakshmi Priya, T.K.S. A Top-Down Survey on Security Aspects of the Internet of Things (IoT). International Journal of Innovative Research in Management, Engineering and Technology, 2019, 4,150-156.
Emira, H.H.A. Authenticating IoT devices issues based on blockchain. Journal of Cybersecurity and Information Management, 2020, 1, 35. DOI: https://doi.org/10.54216/JCIM.010202
Reyna, A., Martín, C., Chen, J., Soler, E. and Díaz, M. On blockchain and its integration with IoT. Challenges and opportunities. Future generation computer systems, 2018, 88, 173-190. DOI: https://doi.org/10.1016/j.future.2018.05.046
Novais, L., Maqueira, J.M. and Ortiz-Bas, Á. A systematic literature review of cloud computing use in supply chain integration. Computers and Industrial Engineering, 2019, 129, 296-314. DOI: https://doi.org/10.1016/j.cie.2019.01.056
Althoubi, A., Alshahrani, R. and Peyravi, H. Delay analysis in IoT sensor networks. Sensors, 2021, 21, 3876. DOI: https://doi.org/10.3390/s21113876
Suryadevara, S. and Ali, S. Preperformance Testing of a Website. In CS and IT Conference Proceedings, CS and IT Conference Proceedings, 2020, 10, 7. DOI: https://doi.org/10.5121/csit.2020.100703