Modeling a LoRAWAN Network for Vehicle Wildlife Collision Avoidance System on Rural Roads

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Abstract

The network of rural roads covers different types of terrain, including forest areas, pastures, arable land and sparsely populated areas. The safety of people and animals is a priority in traffic on these roads. Early detection of pedestrians, animals and other moving objects along the road can significantly reduce the risk of accidents. As part of this research, a sensor system is being developed that can detect characteristics of living things in motion, such as unexpectedly crossing the road without clear signs. Such timely detection of moving objects enables adequate preventive measures and reduces potential traffic accidents. The consequences of traffic accidents of this type can cause serious damage to animals and people property, and road infrastructure. The topicality of this problem at the spatial and seasonal level is emphasized in studies that identify the hotspots of these accidents. Factors such as traffic characteristics and road infrastructure are key to modeling protective systems on rural roads. The presented study investigates the deployment of sensor nodes and LoRAWAN gateways for wildlife detection on rural roads, with the aim of reducing the risk of traffic accidents caused by Wildlife-Vehicle Collisions.

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