Abstract: The increase of the population living in cities has put a lot of pressure in urban transportation systems. It comes, among other things, with noteworthy air pollution, time and energy wastage, and drivers´ discomfort due to parking spots scarcity. Finding a parking spot has become a major problem for drivers. To overcome this problem, smart parking services that detect parking spot occupancy status and inform drivers about their availability have been proposed. The deployment of these solutions is reducing the costs associated to traffic jams or gas consumption. However, one of the main challenges faced when planning and deploying this kind of service is the communication technology used by the parking sensors, which are typically buried under the asphalt, as it has to cover large areas of the city in the most cost-effective way. In this paper, we analyze the behavior and performance of a LoRaWAN network supporting the smart parking service in the city of Santander. The sensors and network deployment are described and the thorough experimental evaluation of the network behavior is presented. The goal of this assessment is to provide insights that could be helpful for better understanding the key factors affecting the communication. The long-termed analysis of the parking sensors deployments studied, have allowed us to derive an experimental propagation model that could be useful for the planning of city-scale IoT infrastructures employing LoRaWAN networks as their wireless access technology. Moreover, we have also analyzed the behavior of the LoRa wireless network in order to evaluate the possibility of leveraging network information to increase the confidence on smart parking sensor readings through AI-based predictors.

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