Abstract
Automation with intelligence has gradually become the community’s talking point around the world. Nowadays, even public transportation such as bus is equipped with video surveillance cameras mainly for monitoring and security purposes. However, they can also be used for other purposes, such as analytics system through passengers counting. This is important to help the bus service provider to improve their fleet management operation by keep tracking of the passenger ridership information. Based on this information, the service provider company can be more flexible with bus scheduling by calculation of lines and stations efficiently. Hence, this paper proposed an analytics system through video footages acquired from daily operation. The incoming and outgoing passengers are tracked based on their head using blob detection and trained MobileNet SSD. The reference line is drawn to make sure that the detected passengers’ head crossed the line before it is considered either as incoming or outgoing passengers. Based on this video analysis, the number of passengers is counted concurrent with the location of the bus. This system is tested in several cases and managed to give proper information for the bus service provider. The data is stored in a cloud database for history, graphically visualize the passenger ridership in a day, month or year. Therefore, this system is able to help the bus company to manage their resource efficiently and consequently improving their service quality and lower the cost of transportation.
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Acknowledgments
This research is a collaboration between School of Computer Sciences, USM with Rapid Penang Sdn. Bhd. and affiliated with Robotics, Computer Vision & Image Processing (RCVIP) Research Group Lab at School of Computer Sciences, Universiti Sains Malaysia. This project is fully funded by USM Short Term Grant (PKOMP/6315262) and partially funded by USM RU Grant (PKOMP/8014001).
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Ab Wahab, M.N., Mohamed, A.S.A., Chung, K.C. (2019). iPassenger: Smart Passenger Analytics System. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2019. Lecture Notes in Computer Science(), vol 11870. Springer, Cham. https://doi.org/10.1007/978-3-030-34032-2_41
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DOI: https://doi.org/10.1007/978-3-030-34032-2_41
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