Social Parking: Applying the Citizens as Sensors Paradigm to Parking Guidance and Information
Julio Barbancho,
Jorge Ropero,
Joaquín Luque,
Alejandro Caraballo and
Carlos León
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Julio Barbancho: Departamento de Tecnología Electrónica, Universidad de Sevilla, 41011 Sevilla, Spain
Jorge Ropero: Departamento de Tecnología Electrónica, Universidad de Sevilla, 41011 Sevilla, Spain
Joaquín Luque: Departamento de Tecnología Electrónica, Universidad de Sevilla, 41011 Sevilla, Spain
Alejandro Caraballo: Department of Software Engineering and Business Solutions, Soltel Company, 41092 Sevilla, Spain
Carlos León: Departamento de Tecnología Electrónica, Universidad de Sevilla, 41011 Sevilla, Spain
Sustainability, 2019, vol. 11, issue 23, 1-19
Abstract:
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.
Keywords: parking guidance and information (PGI); intelligent transportation systems (ITS); ontology; data mining; forecast algorithm; citizens as sensors; smart cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:23:p:6549-:d:289043
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