{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:47:20Z","timestamp":1774367240199,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2015,7,3]],"date-time":"2015-07-03T00:00:00Z","timestamp":1435881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mobility management represents one of the most important parts of the smart city concept. The way we travel, at what time of the day, for what purposes and with what transportation modes, have a pertinent impact on the overall quality of life in cities. To manage this process, detailed and comprehensive information on individuals\u2019 behaviour is needed as well as effective feedback\/communication channels. In this article, we explore the applicability of crowdsourced data for this purpose. We apply a gradient boosting  trees algorithm to model individuals\u2019 mobility decision making processes (particularly concerning what transportation mode they are likely to use). To accomplish this we rely on data collected from three sources: a dedicated smartphone application, a geographic information systems-based web interface and weather forecast data collected over a period of six months. The applicability of the developed model is seen as a potential platform for personalized mobility management in smart cities and a communication tool between the city (to steer the users towards more sustainable behaviour by additionally weighting preferred suggestions) and users (who can give feedback on the acceptability of the provided suggestions, by accepting or rejecting them, providing an additional input to the learning process).<\/jats:p>","DOI":"10.3390\/s150715974","type":"journal-article","created":{"date-parts":[[2015,7,3]],"date-time":"2015-07-03T16:19:37Z","timestamp":1435940377000},"page":"15974-15987","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Smart City Mobility Application\u2014Gradient Boosting Trees for Mobility Prediction and Analysis Based on Crowdsourced Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2795-8094","authenticated-orcid":false,"given":"Ivana","family":"Semanjski","sequence":"first","affiliation":[{"name":"Department of Telecommunications and Information Processing, Gent University,  St-Pietersnieuwstraat 41, Gent B-9000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5628-6974","authenticated-orcid":false,"given":"Sidharta","family":"Gautama","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing, Gent University,  St-Pietersnieuwstraat 41, Gent B-9000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,7,3]]},"reference":[{"key":"ref_1","unstructured":"Giffinger, R., Fertner, C., Kramar, H., Kalasek, R., Pichler-Milanovic, N., and Meijers, E. 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Available online: http:\/\/www.wunderground.com\/weather\/api\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/7\/15974\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:43Z","timestamp":1760215723000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/7\/15974"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,7,3]]},"references-count":31,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2015,7]]}},"alternative-id":["s150715974"],"URL":"https:\/\/doi.org\/10.3390\/s150715974","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,7,3]]}}}