{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:54:49Z","timestamp":1771703689643,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Smart Cities"],"abstract":"<jats:p>The development of crowdsensing-based technologies has allowed for the use of smartphones in large-scale data collection for different scopes of applications, mostly in a transparent and ubiquitous way. When concerning urban areas and smart city initiatives, the collection and further analysis of information about the highest number of vehicles is of paramount importance, potentially supporting more efficient mobility planning and management actions in modern cities. In this context, this article proposes a public general-purpose platform for acquisition and visualization of vehicular speeds, which can then be exploited by any additional application. For that, a crowdsensing-based mobile software application was developed to collect instantaneous speeds provided by smartphone GPS, formatting and distributing this information to a database system. Such historical data can then be exported or visualized through a web-based comprehensive interface, which provides valuable data when planning traffic mobility in cities; for example, indicating areas with heavier traffic over a certain time period. Therefore, allowing the use of many different search filters and supporting data delivery in the JSON format, the CitySpeed platform can provide services not supported by popular applications, such as Waze and Google Maps, and potentially assist smart city initiatives in this area.<\/jats:p>","DOI":"10.3390\/smartcities2010004","type":"journal-article","created":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T11:19:58Z","timestamp":1549019998000},"page":"46-65","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["CitySpeed: A Crowdsensing-Based Integrated Platform for General-Purpose Monitoring of Vehicular Speeds in Smart Cities"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3988-8476","authenticated-orcid":false,"given":"Daniel G.","family":"Costa","sequence":"first","affiliation":[{"name":"Department of Technology, State University of Feira de Santana, Feira de Santana 44036-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4179-4938","authenticated-orcid":false,"given":"Adson","family":"Damasceno","sequence":"additional","affiliation":[{"name":"Applied Computing Graduation Program, State University of Feira de Santana, Feira de Santana 44036-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0116-6489","authenticated-orcid":false,"given":"Ivanovitch","family":"Silva","sequence":"additional","affiliation":[{"name":"Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1016\/j.envsoft.2005.04.012","article-title":"Determining a sustainable city model","volume":"21","author":"Egger","year":"2006","journal-title":"Environ. 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