Abstract
This article explores the key aspects and challenges in transforming the postal and package delivery networks to a fully automated and self-learning stage. It analyzes its current state, possible gaps in research and business solutions, identifying the existing technologies, and the possible management challenges. The authors also consider socio-economic factors during the current context analysis stage. The authors reviewed the literature and identified best practices and technological solutions used in the postal delivery field and existing research gaps. The most commonly pointed technological solutions include for example IoT for package tracking and machine learning with big data for workload optimization. A case study with company stakeholders in the form of interview was followed, to identify the best practices used and technological issues in the field. The researchers analyzed the current state and introduced the potential advancements of the target state - a more efficient, technology-driven postal delivery system.
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References
Hakim, I.M., Putriandita, A.: Designing implementation strategy for Internet of Things (IoT) on logistic transportation sector in Indonesia. In: Proceedings of the 4th International Conference on Industrial and Business Engineering, pp. 23–28. ACM, Macau Macao (2018). https://doi.org/10.1145/3288155.3288165
Gupta, M., Garg, N., Garg, J., Gupta, V., Gautam, D.: Designing an intelligent parcel management system using IoT & machine learning. In: 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), pp. 751–756. IEEE, Arad, Romania (2022). https://doi.org/10.1109/GlobConET53749.2022.9872449
Ilyashenko, O., Kovaleva, Y., Burnatcev, D., Svetunkov, S.: Automation of business processes of the logistics company in the implementation of the IoT. IOP Conf. Ser.: Mater. Sci. Eng. 940, 012006 (2020). https://doi.org/10.1088/1757-899X/940/1/012006
Golubchikov, O., Thornbush, M.: Artificial intelligence and robotics in smart city strategies and planned smart development. Smart Cities. 3, 1133–1144 (2020). https://doi.org/10.3390/smartcities3040056
Nagenborg, M.: Urban robotics and responsible urban innovation. Ethics Inf. Technol. 22, 345–355 (2020). https://doi.org/10.1007/s10676-018-9446-8
Miguel Jaller, C.O.-P.: Jobs and Automated Freight Transportation: How Automation Affects the Freight Industry and What to Do About It (2022). https://doi.org/10.7922/G2SX6BHW
Kaup, S., Ludwig, A., Franczyk, B.: Framework Artifact for the Road-Based Physical Internet based on Internet Protocols (2021). https://doi.org/10.35090/GATECH/7883
Ehrentraut, F., Landschützer, C., Jodin, D., Graf, H.-C., Gasperlmair, A.: A case study derived methodology to create a roadmap to realize the Physical Internet for SME. In: Proceedings of the 3rd International Physical Internet Conference, Atlanta, GA, USA (2016)
Ballot, E., et al.: Roadmap to the Physical Internet. Executive version (2020). https://www.etp-logistics.eu/wp-content/uploads/2022/11/Roadmap-to-Physical-Intenet-Executive-Version_Final-web.pdf,
Balfaqih, M., Balfagih, Z., Lytras, M.D., Alfawaz, K.M., Alshdadi, A.A., Alsolami, E.: A blockchain-enabled IoT logistics system for efficient tracking and management of high-price shipments: a resilient, scalable and sustainable approach to smart cities. Sustainability. 15, 13971 (2023). https://doi.org/10.3390/su151813971
Yao, Y., et al.: Internet of Things positioning technology based intelligent delivery system. IEEE Trans. Intell. Transport. Syst. 24, 12862–12876 (2023). https://doi.org/10.1109/TITS.2022.3155638
Ratasuk, R., Mangalvedhe, N., Zhang, Y., Robert, M., Koskinen, J.-P.: Overview of narrowband IoT in LTE Rel-13. In: 2016 IEEE Conference on Standards for Communications and Networking (CSCN), pp. 1–7 (2016). https://doi.org/10.1109/CSCN.2016.7785170
He, Y., Csiszár, C.: Model for crowdsourced parcel delivery embedded into mobility as a service based on autonomous electric vehicles. Energies 14, 3042 (2021). https://doi.org/10.3390/en14113042
Kassai, E.T., Azmat, M., Kummer, S.: Scope of Using Autonomous Trucks and Lorries for Parcel Deliveries in Urban Settings. Logistics. 4, 17 (2020). https://doi.org/10.3390/logistics4030017
Gao, C., Wang, G., Shi, W., Wang, Z., Chen, Y.: Autonomous driving security: state of the art and challenges. IEEE Internet Things J. 9, 7572–7595 (2022). https://doi.org/10.1109/JIOT.2021.3130054
Gopinath, A., Sivakumar, S., Ranjani, D., Kumari, S., Perumal, V., Prakash, R.B.R.: A communication system built on the internet of things for fully autonomous electric cars. In: 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1515–1520. IEEE, Madurai, India (2023). https://doi.org/10.1109/ICICCS56967.2023.10142320
Bautista, C., Mester, G.: Internet of Things in self-driving cars environment. Interdiscip. Descr. Complex Syst. 21, 188–198 (2023). https://doi.org/10.7906/indecs.21.2.8
Zhu, X., Cai, L., Lai, P.-L., Wang, X., Ma, F.: Evolution, challenges, and opportunities of transportation methods in the last-mile delivery process. Systems. 11, 509 (2023). https://doi.org/10.3390/systems11100509
Sina Mohri, S., Nassir, N., Thompson, R.G., Ghaderi, H.: Last-Mile logistics with on-premises parcel Lockers: who are the real Beneficiaries? Tran. Res. Part E: Logist. Trans. Rev. 183, 103458 (2024). https://doi.org/10.1016/j.tre.2024.103458
Kuznetsova, G.V., Podbiralina, G.V.: Transport digitalization. In: Kahraman, C., Haktanır, E. (eds.) Intelligent Systems in Digital Transformation, pp. 579–608. Springer International Publishing, Cham (2023). https://doi.org/10.1007/978-3-031-16598-6_25
Wanganoo, L., Patil, A.: Preparing for the smart cities: IoT enabled last-mile delivery. In: 2020 Advances in Science and Engineering Technology International Conferences (ASET), pp. 1–6. IEEE, Dubai, United Arab Emirates (2020). https://doi.org/10.1109/ASET48392.2020.9118197
Tang, Y.M., Chau, K.Y., Xu, D., Liu, X.: Consumer perceptions to support IoT based smart parcel locker logistics in China. J. Retail. Consum. Serv. 62, 102659 (2021). https://doi.org/10.1016/j.jretconser.2021.102659
Wang, G., Listya, M., Alianto, H., Nugroho, D.A.: Real time tracking system integrated with iot for package delivery in Indonesia’s logistic company with TOGAF Implementation. In: 2023 10th International Conference on ICT for Smart Society (ICISS), pp. 1–4. IEEE, Bandung, Indonesia (2023). https://doi.org/10.1109/ICISS59129.2023.10291211
Kieras, T., Farooq, J., Zhu, Q.: I-SCRAM: a framework for iot supply chain risk analysis and mitigation decisions. IEEE Access. 9, 29827–29840 (2021). https://doi.org/10.1109/ACCESS.2021.3058338
Tawalbeh, L., Muheidat, F., Tawalbeh, M., Quwaider, M.: IoT privacy and security: challenges and solutions. Appl. Sci. 10, 4102 (2020). https://doi.org/10.3390/app10124102
Abdolinezhad, S., Schappacher, M., Sikora, A.: Secure wireless architecture for communications in a parcel delivery system. In: 2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS), pp. 1–6. IEEE, Dortmund, Germany (2020). https://doi.org/10.1109/IDAACS-SWS50031.2020.9297086
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Tulev, U., Shevtshenko, E., Ermus, I. (2024). Evaluating Postal Systems’ Current State, Roadmap to Automation. In: Camarinha-Matos, L.M., Ferrada, F. (eds) Technological Innovation for Human-Centric Systems. DoCEIS 2024. IFIP Advances in Information and Communication Technology, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-031-63851-0_20
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