Abstract
Geolocation data is fundamental to businesses relying on vehicles such as logistics and transportation. With the advance of the technology, collecting geolocation data become increasingly accessible and affordable, which raised new opportunities for business intelligence. This paper addresses the application of geolocation data for monitoring logistics processes, namely for detecting vehicle-based operations in real time. A stream of geolocation entries is used for inferring stationary events. Data from an international logistics company is used as a case study, in which operations of loading/unloading of goods are not only identified but also quantified. The results of the case study demonstrate the effectiveness of the solution, showing that logistics operations can be inferred from geolocation data. Further meaningful information may be extracted from these inferred operations using process mining techniques.
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Acknowledgements
This work is financed by the European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project PTDC/ECI-TRA/32053/2017 - POCI-01-0145-FEDER-032053. Tânia Fontes also thanks FCT for the Post-Doctoral scholarship SFRH/BPD/109426/2015.
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Ribeiro, J., Tavares, J., Fontes, T. (2022). Real-Time Detection of Vehicle-Based Logistics Operations. In: Martins, A.L., Ferreira, J.C., Kocian, A. (eds) Intelligent Transport Systems. INTSYS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 426. Springer, Cham. https://doi.org/10.1007/978-3-030-97603-3_14
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