Simulation Modeling of An IoT Based Cold Chain Logistics Management System

Celal Çeken; Dini Abdurahman

doi:10.35377/saucis.02.02.598963

TR EN

IoT Tabanlı Soğuk Zincir Lojistik Yönetim Sisteminin Benzetim Modellemesi

Öz

Dünya ekonomisinde görülen çarpıcı büyüme, lojistik hizmetin çevik, esnek ve duyarlı olmasını isteyen tedarik zinciri endüstrisinide hızlandırmaktadır. İnternet teknolojileri, müşteri ve lojistik sağlayıcı arasındaki bilgi aktarımı konusunda oldukça başarılıdırlar. Bununla birlikte, lojistik hizmetindeki mal akışı ile bilgi akışı arasındaki mevcut boşluk, sıcaklığa duyarlı ürünler hakkında gerçek zamanlı bilgi edinme konusunda bir sorun teşkil etmektedir ve bu da lojistik yönetimini karar vericiler açısından daha zorlu hale getirmektedir. Nesnelerin İnterneti teknolojisi, soğuk zincir endüstrisinde ortam görüntüleme, yönetim ve karar alma süreçleri açısından umut verici bir çözüm gibi görünmektedir. Bu çalışma, soğuk zincirin gerçek zamanlı ortam sıcaklığını yöneterek, izleyerek ve sıcağa duyarlı ürünlerin raf ömrünü tahmin ederek tüm aktörlerin karar desteğini geliştirmeye yardımcı olan Nesnelerin İnterneti tabanlı bir soğuk zincir lojistiği önermektedir. Bu ön çalışmada, ortam parametrelerinin gerçek zamanlı verileri IEEE 802.15.4 tabanlı kablosuz algılayıcı ağları kullanılarak toplanmış ve bir ağ geçidi üzerinden uzak sunucuya aktarılarak ürünlerin raf ömrünün karar destek sistemi tarafından tahmin edilebilmesi sağlanmıştır. Geliştirilen uygulama çerisinde, soğuk zincirde bulunan bozulabilir ürünlerin tanımlanmasıyla amacıyla radyo frekanslı tanımlama (RFID) sistemi de modellenmiştir.

Anahtar Kelimeler

Nesnelerin İnterneti,Soğuk Zincir Lojistiği,Kablosuz Algılayıcı Ağlar,Raf Ömrü

Simulation Modeling of An IoT Based Cold Chain Logistics Management System

Abstract

The dramatic growth of the world economy has been accelerated the supply chain industry which demands logistics service to be agile, flexible and responsive. Internet technology is quite successful in transferring information between customer and logistics provider. However, the existing gap between goods flow and information flow in logistic service has created a problem in getting real-time information about temperature-sensitive items, which makes logistics management more challenging for decision-makers. Internet of Things technology seems a promising solution for monitoring, managing, and decision making in cold chain industries. This study proposes an Internet of Things based cold chain logistics that help to enhance the decision support of all actors through managing, monitoring the real-time ambient temperature of the cold chain and predicting the shelf life of temperature-sensitive products. In this preliminary study, real-time data of ambient parameters are gathered using IEEE 802.15.4 based wireless sensor networks and transferred to the remote server through a gateway so that the shelf life of the products can be predicted by the decision support system. Radio Frequency Identification (RFID) is also modeled for further considerations related to the identification issue of perishable products inside the cold chain.

Keywords

Internet of Things,Cold Chain Logistics,Wireless Sensor Networks,Shelf Life

Supporting Institution

SRPC (BAPK) Unit of Sakarya University

Project Number

2013-12-10-004

References

S. Mejjaoulia and R. F. Babiceanu, “RFID-wireless sensor networks integration: Decision models and optimization of logistics systems operations,” Journal of Manufacturing Systems, vol. 35, pp. 234-245, 2015.
Food wastage footprint: Impacts on Natural Resources, 2013. [Online]. Available: http://www.fao.org/docrep/018/i3347e/i3347e.pdf. [Accessed: 2019].
Cost-Effective, Real-Time System to Tackle $35 Billion Annual Waste in U.S. Perishable Goods, 2006. [Online]. Available: http://www.prnewswire.com/news-releases/cost-effective-real-time-system-to-tackle-35-billion-annual-waste-in-us-perishable-goods-56420232.html. [Accessed: 2017].
J. C. Park, “Mobile RFID reader-initiated LLRP connection,” IEEE Int. Conf. Comput. Convergence Technol, pp. 1205-1209, 2012.
F. Li and Z. Chen, “Brief analysis of application of RFID in pharmaceutical cold-chain temperature monitoring system,” Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), pp. 2418–2420, 2011.
H. Ding, R. Li, S. Li, J. Han and J. Zhao, “MISS: Multi-dimensional Information Sensing Surveillance for Cold Chain Logistics,” IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems, pp. 519-523, 2013.
R. Porkodi and V. Bhuvaneswari, “The Internet of Things (IoT) Applications and Communication Enabling Technology Standards: An Overview,” 2014 International Conference on Intelligent Computing Applications, pp. 324-329, 2014.
Internet of Things European Research Cluster, “The Internet of Things,” New Horizons, 2012.

B. Yan and D. Lee Lee, “Application of RFID in cold chain temperature monitoring system,” ISECS International Colloquium on Computing, Communication, Control, and Management, pp. 258-261. 2009.
J. P. Rodrigue and T. Notteboom “The Cold Chain and its Logistics,” The Geography of Transport Systems, 2017. [Online]. Available: https://people.hofstra.edu /geotrans/eng/ch5en/appl5en /ch5a5en.html. [Accessed: July 2019].
Outlook on the Logistics & Supply Chain Industry. World Economic Forum, 2013.
S. Nechifor, A. Petrescu, D. Damian, D. Puiu and B. Târnaucă, “Predictive analytics based on CEP for logistic of sensitive goods,” International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), pp. 817-822, 2014.
A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” IEEE Communications Surveys & Tutorials, vol. 17, pp. 2347-2376, 2015.
J. Banks, M. A. Pachano, L. G. Thompson and D. Hanny, “RFID Applied,” John Wiley & Sons Inc. 2007.
EPC™ Radio-Frequency Identity Protocols Generation-2 UHF RFID, GS1 EPCglobal Inc., 2013.
A. Van Nieuwenhuyse, A. Koubaa and M. Alves, “On the use of the ZigBee protocol for Wireless Sensor Networks,” IPP-HURRAY Research Group, 2006.
M. A. V. Boekel, “Kinetic Modeling of Food Quality : A Critical Review,” Comprehensive Reviews in Food Science and Food Safety, vol. 7(1), pp. 144–158, 2008.
T. P. Labuza, “Application of chemical kinetics to deterioration of foods,” J. Chem. Educ, vol. 61(4), pp. 348, 1984.

Details

Primary Language

English

Subjects

Communication and Media Studies

Journal Section

Research Article

Authors

Celal Çeken
0000-0002-6912-0057
Türkiye

Dini Abdurahman ^*
0000-0002-6912-0057
Türkiye

Publication Date

August 29, 2019

Submission Date

July 30, 2019

Acceptance Date

August 28, 2019

Published in Issue

Year 2019 Volume: 2 Number: 2

DOI

https://doi.org/10.35377/saucis.02.02.598963

IZ

https://izlik.org/JA99UR79KD

Cite

RIS / Bibtex

APA

Çeken, C., & Abdurahman, D. (2019). Simulation Modeling of An IoT Based Cold Chain Logistics Management System. Sakarya University Journal of Computer and Information Sciences, 2(2), 89-100. https://doi.org/10.35377/saucis.02.02.598963

AMA

1.Çeken C, Abdurahman D. Simulation Modeling of An IoT Based Cold Chain Logistics Management System. SAUCIS. 2019;2(2):89-100. doi:10.35377/saucis.02.02.598963

Chicago

Çeken, Celal, and Dini Abdurahman. 2019. “Simulation Modeling of An IoT Based Cold Chain Logistics Management System”. Sakarya University Journal of Computer and Information Sciences 2 (2): 89-100. https://doi.org/10.35377/saucis.02.02.598963.

EndNote

Çeken C, Abdurahman D (August 1, 2019) Simulation Modeling of An IoT Based Cold Chain Logistics Management System. Sakarya University Journal of Computer and Information Sciences 2 2 89–100.

IEEE

[1]C. Çeken and D. Abdurahman, “Simulation Modeling of An IoT Based Cold Chain Logistics Management System”, SAUCIS, vol. 2, no. 2, pp. 89–100, Aug. 2019, doi: 10.35377/saucis.02.02.598963.

ISNAD

Çeken, Celal - Abdurahman, Dini. “Simulation Modeling of An IoT Based Cold Chain Logistics Management System”. Sakarya University Journal of Computer and Information Sciences 2/2 (August 1, 2019): 89-100. https://doi.org/10.35377/saucis.02.02.598963.

JAMA

1.Çeken C, Abdurahman D. Simulation Modeling of An IoT Based Cold Chain Logistics Management System. SAUCIS. 2019;2:89–100.

MLA

Çeken, Celal, and Dini Abdurahman. “Simulation Modeling of An IoT Based Cold Chain Logistics Management System”. Sakarya University Journal of Computer and Information Sciences, vol. 2, no. 2, Aug. 2019, pp. 89-100, doi:10.35377/saucis.02.02.598963.

Vancouver

1.Celal Çeken, Dini Abdurahman. Simulation Modeling of An IoT Based Cold Chain Logistics Management System. SAUCIS. 2019 Aug. 1;2(2):89-100. doi:10.35377/saucis.02.02.598963