Abstract
The paper proposes a hybrid wireless network, which can be installed on a roadside to detect passing vehicles and recognize their classes. The vehicle detection and classification tasks are performed by analyzing strength of a radio signal received from Bluetooth Low Energy beacons with the use of machine learning algorithms. The introduced system is cost-efficient, easy to install, and can be used for a long time without an external power source. An energy-aware algorithm is proposed, which uses a scheduling mechanism to manage wireless nodes that can act as BLE beacons (in low energy mode) or receivers. Results of experimental evaluation confirm that the proposed solution enables collection of accurate traffic data in real time and prolongs lifetime of battery-powered wireless nodes in the traffic monitoring system. The paper also discusses the applicability of various wireless communication technologies and the influence of wireless node location on vehicle detection accuracy.
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Acknowledgement
The research was supported by The National Centre for Research and Development (NCBR) grant number LIDER/18/0064/L-7/15/NCBR/2016.
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Bernas, M., Płaczek, B., Korski, W. (2018). Wireless Network with Bluetooth Low Energy Beacons for Vehicle Detection and Classification. In: Gaj, P., Sawicki, M., Suchacka, G., Kwiecień, A. (eds) Computer Networks. CN 2018. Communications in Computer and Information Science, vol 860. Springer, Cham. https://doi.org/10.1007/978-3-319-92459-5_34
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DOI: https://doi.org/10.1007/978-3-319-92459-5_34
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