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Logistics and Freight Transportation Management: An NLP based Approach for Shipment Tracking

Rachit Garg, Arvind Wamanrao Kiwelekar and Laxman Damodar Netak

Pertanika Journal of Science & Technology, Pre-Press

DOI: https://doi.org/10.47836/pjst.29.4.28

Published: 2021-10-18

Tracking and tracing systems have become basic services for most logistics companies and are particularly essential for the shipping and logistics industry. Dynamic logistics management today need constant supervision and management of continuously-changing supply chains that motivate the necessity of goods-centric logistics monitoring and tracking, which guarantees a chance to improve transparency and control of a company’s multiple logistical activities. However, operational inefficiencies due to the conventional monitoring system for the supply chain management can also result in sales loss, higher cost, poor customer service–and eventually lower profits. Based on research literature, this paper aims to provide a novel approach for tracking and tracing shipment in a logistics organisation by implementing deep natural language processing concepts. The study aims to allow the stakeholders to think in new ways in their organisation and helping them to have a powerful influence on tracking and tracing to make the best decision possible at the right time. The proposed method is compared based on the accuracy of identifying the query, and results are significantly acceptable. This study is of related interest to researchers, academicians, and practitioners.

  • Abbas, K., Afaq, M., Khan, T. A., & Song, W. C. (2020). A blockchain and machine learning-based drug supply chain management and recommendation system for smart pharmaceutical industry. Electronics, 9(5), Article 852. https://doi.org/10.3390/electronics9050852

  • Ahkouk, K., Machkour, M., & Antari, J. (2020). Inferring SQL queries using interactivity. In Proceedings of the 3rd International Conference on Networking, Information Systems & Security (pp. 1-7). ACM Publishing. https://doi.org/10.1145/3386723.3387820

  • Artto, K., Heinonen, R., Arenius, M., Kovanen, V., & Nyberg, T. (1998). Global project business and the dynamics of change. Technology Development Centre Finland and Project Management Association Finland.

  • Bai, T., Ge, Y., Guo, S., Zhang, Z., & Gong, L. (2021). Enhanced natural language interface for web-based information retrieval. IEEE Access, 9, 4233-4241. https://doi.org/10.1109/ACCESS.2020.3048164

  • Bank, W. (2019). Trade integration as a pathway to development? LAC Semiannual Report. World Bank.

  • Baresi, L., Meroni, G., & Plebani, P. (2016). A GSM-based approach for monitoring cross-organization business processes using smart objects. In International Conference on Business Process Management (pp. 389-400). Springer. https://doi.org/10.1007/978-3-319-42887-1_32

  • Betti, Q., Khoury, R., Halle, S., & Montreuil, B. (2019). Improving hyperconnected logistics with blockchains and smart contracts. IT Professional, 21(4), 25-32. https://doi.org/10.1109/MITP.2019.2912135

  • Brewer, A., Sloan, N., & Landers, T. L. (1999). Intelligent tracking in manufacturing. Journal of Intelligent Manufacturing, 10(3), 245-250. https://doi.org/10.1023/A:1008995707211

  • Chadil, N., Russameesawang, A., & Keeratiwintakorn, P. (2008). Real-time tracking management system using GPS, GPRS and Google earth. In 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (Vol. 1, pp. 393-396). IEEE Publishing. https://doi.org/10.1109/ECTICON.2008.4600454

  • Chary, M., Parikh, S., Manini, A. F., Boyer, E. W., & Radeos, M. (2019). A review of natural language processing in medical education. Western Journal of Emergency Medicine, 20(1), 78-86. https://doi.org/10.5811/westjem.2018.11.39725

  • Chowdhary, K. R. (2020). Natural language processing. In Fundamentals of Artificial Intelligence (pp. 603-649). Springer. https://doi.org/10.1007/978-81-322-3972-7_19

  • Christidis, K., & Devetsikiotis, M. (2016). Blockchains and smart contracts for the internet of things. IEEE Access, 4, 2292-2303. https://doi.org/10.1109/ACCESS.2016.2566339

  • Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1-14. https://doi.org/10.1108/09574090410700275

  • Clark, A., Fox, C., & Lappin, S. (2010). The handbook of computational linguistics and natural language processing. Wiley-Blackwell. https://doi.org/10.1002/9781444324044

  • Couderc, B., & Ferrero, J. (2015, June 22-25). fr2sql: Interrogation de bases de données en français [Querying databases in French]. In 22ème Traitement Automatique des Langues Naturelles (pp. 1-13). Caen, France.

  • Garg, R., Kiwelekar, A. W., Netak, L. D., & Bhate, S. S. (2021a). Personalization of news for a logistics organisation by finding relevancy using NLP. In V. K. Gunjan & J. M. Zurada (Eds.), Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Latest Trends in AI, Volume 2 (pp. 215-226). Springer. https://doi.org/10.1007/978-3-030-68291-0_16

  • Garg, R., Kiwelekar, A. W., Netak, L. D., & Bhate, S. S. (2021b). Potential use-cases of natural language processing for a logistics organization. In V. K. Gunjan & J. M. Zurada (Eds.), Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Latest Trends in AI, Volume 2 (pp. 157-191). Springer. https://doi.org/10.1007/978-3-030-68291-0_13

  • Garg, R., Kiwelekar, A. W., Netak, L. D., & Ghodake, A. (2021c). i-Pulse: A NLP based novel approach for employee engagement in logistics organization. International Journal of Information Management Data Insights, 1(1), Article 100011. https://doi.org/10.1016/j.jjimei.2021.100011

  • GEP. (2018). Artificial intelligence and its impact on procurement and supply chain: A comprehensive study. Retrieved May 9, 2020, from https://www.gep.com/white-papers/artificial-intelligence-impact-on-procurement-supply-chain

  • Gnimpieba, Z. D. R., Nait-Sidi-Moh, A., Durand, D., & Fortin, J. (2015). Using internet of things technologies for a collaborative supply chain: Application to tracking of pallets and containers. Procedia Computer Science, 56, 550-557. https://doi.org/10.1016/j.procs.2015.07.251

  • Goll, D. C., & Bolte, N. O. (2020). Potential analysis of track-and-trace systems in the outbound logistics of a Swedish retailer (MSc Thesis). Jonkoping University, Sweden.

  • He, W., Tan, E. L., Lee, E. W., & Li, T. Y. (2009). A solution for integrated track and trace in supply chain based on RFID & GPS. In 2009 IEEE Conference on Emerging Technologies & Factory Automation (pp. 1-6). IEEE Publishing. https://doi.org/10.1109/ETFA.2009.5347146

  • Huang, W. C., Hayashi, T., Wu, Y. C., Kameoka, H., & Toda, T. (2019). Voice transformer network: Sequence-to-Sequence voice conversion using transformer with text-to-speech pretraining. ArXiv Publishing.

  • Huvio, E., Grönvall, J., & Främling, K. (2002, June 13-14). Tracking and tracing parcels using a distributed computing approach. In Proceedings of the 14th Annual Conference for Nordic Researchers in Logistics (NOFOMA’2002) (pp. 29-43). Trondheim, Norway.

  • Jedermann, R., Behrens, C., Westphal, D., & Lang, W. (2006). Applying autonomous sensor systems in logistics - Combining sensor networks, RFIDs and software agents. Sensors and Actuators A: Physical, 132(1), 370-375. https://doi.org/10.1016/j.sna.2006.02.008

  • Kärkkäinen, M., Ala‐Risku, T., & Främling, K. (2004). Efficient tracking for short‐term multi‐company networks. International Journal of Physical Distribution & Logistics Management, 34(7), 545-564. https://doi.org/10.1108/09600030410552249

  • Kerr, A. (1989). Information technology - Creating strategic opportunities for logistics. International Journal of Physical Distribution & Materials Management, 19(5), 15-17. https://doi.org/10.1108/EUM0000000000319

  • Kim, H. M., & Laskowski, M. (2018). Toward an ontology-driven blockchain design for supply-chain provenance. Intelligent Systems in Accounting, Finance and Management, 25(1), 18-27. https://doi.org/10.1002/isaf.1424

  • Klein, T., & Thomas, A. (2009). Opportunities to reconsider decision making processes due to auto-ID. International Journal of Production Economics, 121(1), 99-111. https://doi.org/10.1016/j.ijpe.2008.04.017

  • Klumpp, M., Kandel, C., & Bioly, S. (2011). A model for mystery shipping in logistics. In 9th International Industrial Simulation Conference 2011, ISC 2011 (pp. 180-184). EUROSIS Publishing.

  • Ko, J. M., Kwak, C., Cho, Y., & Kim, C. O. (2011). Adaptive product tracking in RFID-enabled large-scale supply chain. Expert Systems with Applications, 38(3), 1583-1590. https://doi.org/10.1016/j.eswa.2010.07.077

  • Kota, L. (2019). Artificial intelligence in logistics. Advanced Logistic Systems - Theory and Practice, 12(1), 47-60. https://doi.org/10.32971/als.2019.004

  • Kothris, D. (2001). Performance assessment of terrestrial and satellite based position location systems. In Second International Conference on 3G Mobile Communication Technologies (3G 2001) (pp. 211-215). IET Digital Library. https://doi.org/10.1049/cp:20010043

  • Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65-83. https://doi.org/10.1016/S0019-8501(99)00113-3

  • Li, J., Wang, W., Ku, W. S., Tian, Y., & Wang, H. (2019). Spatialnli: A spatial domain natural language interface to databases using spatial comprehension. In Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (pp. 339-348). ACM Publishing. https://doi.org/10.1145/3347146.3359069

  • Liu, D., Li, Y., & Thomas, M. A. (2017). A Roadmap for natural language processing research in information systems. In Proceedings of the 50th Hawaii International Conference on System Sciences. HICSS Publishing. https://doi.org/10.24251/HICSS.2017.132

  • Loebbecke, C., & Powell, P. (1998). Competitive advantage from IT in logistics: The integrated transport tracking system. International Journal of Information Management, 18(1), 17-27. https://doi.org/10.1016/S0268-4012(97)00037-6

  • Lund, S., Manyika, J., Woetzel, J., Bughin, J., Krishnan, M., Seong, J., & Muir, M. (2019). Globalization in transition: The future of trade and value chains. McKinsey Global Institute.

  • MarineCadastre.gov. (2013). AIS data handler. BOEM Publishing.

  • Musa, A., Gunasekaran, A., & Yusuf, Y. (2014). Supply chain product visibility: Methods, systems and impacts. Expert Systems with Applications, 41(1), 176-194. https://doi.org/10.1016/j.eswa.2013.07.020

  • Neumann, M., King, D., Beltagy, I., & Ammar, W. (2019). Scispacy: Fast and robust models for biomedical natural language processing. ArXiv Publishing.

  • Ruiz-Garcia, L., Steinberger, G., & Rothmund, M. (2010). A model and prototype implementation for tracking and tracing agricultural batch products along the food chain. Food Control, 21(2), 112-121. https://doi.org/10.1016/j.foodcont.2008.12.003

  • Shamsuzzoha, A. H. M., Ehrs, M., Tenkorang, R. A., Nguyen, D., & Helo, P. T. (2013). Performance evaluation of tracking and tracing for logistics operations. International Journal of Shipping and Transport Logistics, 5(1), 31-54. https://doi.org/10.1504/IJSTL.2013.050587

  • Sullivan, G., & Fordyce, K. (1989). Logistics management system: Continuous flow manufacturing using knowledge based expert systems. In Proceedings of the 2nd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems-Volume 2 (pp. 520-522). ACM Publishing. https://doi.org/10.1145/67312.67313

  • Sultana, S., Tahsin, M., Reza, T., & Hossam-E-Haider, M. (2016). An innovative implementation of indoor positioning system using GPS. In 2016 3rd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT) (pp. 1-4). IEEE Publishing. https://doi.org/10.1109/CEEICT.2016.7873117

  • Thessen, A. E., Cui, H., & Mozzherin, D. (2012). Applications of natural language processing in biodiversity science. Advances in Bioinformatics, 2012, 1-17. https://doi.org/10.1155/2012/391574

  • Töyrylä, I. (1998). Realising the potential of traceability - A case study research on usage and impacts of product traceability. In Acta Polytechnica Scandinavica Mathematics and Computing Series (Vol. 97). Helsinki University of Technology.

  • Wang, C., Tang, Y., Ma, X., Wu, A., Okhonko, D., & Pino, J. (2020). fairseq S2T: Fast Speech-to-text modeling with fairseq. ArXiv Publishing.

  • Wang, W., Tian, Y., Wang, H., & Ku, W. S. (2020). A natural language interface for database: Achieving transfer-learnability using adversarial method for question understanding. In 2020 IEEE 36th International Conference on Data Engineering (ICDE) (pp. 97-108). IEEE Publishing. https://doi.org/10.1109/ICDE48307.2020.00016

  • Yang, G. H., Xu, K., & Li, V. O. K. (2010). Hybrid cargo-level tracking system for logistics. In 2010 IEEE 71st Vehicular Technology Conference (pp. 1-5). IEEE Publishing. https://doi.org/10.1109/VETECS.2010.5493655

  • Yuksel, M. E., & Yuksel, A. S. (2011). RFID technology in business systems and supply chain management. Journal of Economic and Social Studies, 1(1), 53-71. https://doi.org/10.14706/JECOSS11115

  • Zhao, J. L., Fan, S., & Yan, J. (2016). Overview of business innovations and research opportunities in blockchain and introduction to the special issue. Financial Innovation, 2(1), Article 28. https://doi.org/10.1186/s40854-016-0049-2

ISSN 0128-7702

e-ISSN 2231-8534

Article ID

JST-2606-2021

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