Smart parking management systems need to keep up with the state of parking spots at all times. This is efficiently accomplished via sensor nodes that detect vehicles and update the system’s state as it changes in real time. When sensor nodes use wireless communication as their primary communication link, the deployment approach becomes important, since it directly affects network connectivity, cost, and lifetime. The main factor to consider when deploying wireless sensor networks (WSN) in parking environments is the prediction of radio frequency (RF) signal propagation. Inaccurate propagation models lead to systems that under- or over-perform, both of which negatively affect WSN performance. Most of the existing RF propagation models are created to support cellular systems environments, which drastically differ from indoor/outdoor parking environments—few or no model exists that accurately predict RF signal propagation in parking environments. Therefore, there is a need for models that accurately characterize RF signal propagation in these environments. This paper proposes empirical path loss models for WSN deployment in indoor and outdoor car parking lots. The proposed models are compared with theoretical models. Theoretical models deviate from the proposed models and the measured values by 10% to 46%. The provided models, as well as the measured data, can be used for efficient planning and deployment of WSN in various proposed smart cities, intelligent transportation, and parking lot systems.
Path Loss Models for Low-Power, Low-Data Rate Sensor Nodes for Smart Car Parking Systems
IEEE Transactions on Intelligent Transportation Systems ; 19 , 6 ; 1774-1783
2018-06-01
3384480 byte
Article (Journal)
Electronic Resource
English
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European Patent Office | 2024
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