{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:17:37Z","timestamp":1787008657209,"version":"build-2736575974"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,5,19]],"date-time":"2020-05-19T00:00:00Z","timestamp":1589846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The concept of smart systems blessed with different technologies can enable many algorithms used in Machine Learning (ML) and the world of the Internet of Things (IoT). In a modern city many different sensors can be used for information collection. Algorithms that are cast-off in Machine Learning improves the capabilities and intelligence of a system when the amount of data collectedincreases. In this research, we propose a TCC-SVM system model to analyse traffic congestion in the environment of a smart city. The proposed model comprises an ML-enabled IoT-based road traffic congestion control system whereby the occurrence of congestion at a specific point is notified.<\/jats:p>","DOI":"10.1093\/comjnl\/bxz129","type":"journal-article","created":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T15:23:19Z","timestamp":1569943399000},"page":"1672-1679","source":"Crossref","is-referenced-by-count":66,"title":["Adaptive IoT Empowered Smart Road Traffic Congestion Control System Using Supervised Machine Learning Algorithm"],"prefix":"10.1093","volume":"64","author":[{"given":"Ayesha","family":"Ata","sequence":"first","affiliation":[{"name":"National College of Business Administration and Economics, Computer Science, Government College University Lahore, Computer Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Adnan","family":"Khan","sequence":"additional","affiliation":[{"name":"National College of Business Administration and Economics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sagheer","family":"Abbas","sequence":"additional","affiliation":[{"name":"National College of Business Administration and Economics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Saleem","family":"Khan","sequence":"additional","affiliation":[{"name":"National College of Business Administration and Economics, Computer Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gulzar","family":"Ahmad","sequence":"additional","affiliation":[{"name":"National College of Business Administration and Economics, Computer Science"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,5,19]]},"reference":[{"key":"2021120104052710500_ref1","article-title":"IoT Based Smart Traffic Density Alarming Indicator","volume":"3","author":"Yashashree","year":"2016","journal-title":"Int. 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