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Nowadays, the problem of parking guidance information (PGI) is one of the great challenges of smart cities. Sensor networks have been traditionally used, but they sometimes constitute a high administrative cost. For this reason, this paper presents social parking, a system that is based on the citizens as sensors paradigm, where data are collected by users and are processed using data mining techniques. Moreover, an ontology is used to enable the standardization of information. This way, social parking is compatible with the FIWARE platform. A forecast algorithm was also designed and verified to estimate the number of free parking spots inside a parking lot. With this aim, we used public parking data from eight parking lots in the city of Zaragoza. Client applications allowed testing of all the functions of the parking system. These tests were carried out in three experimental parking lots in the city of Málaga.

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