{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T01:59:20Z","timestamp":1771466360755,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T00:00:00Z","timestamp":1721952000000},"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 safety of cyclists on city streets is a significant concern, particularly with the rising number of accidents in densely populated areas. Urban environments present numerous challenges, such as complex road networks and heavy traffic, which increase the risk of cycling-related incidents. Such concern has been recurrent, even within smart city scenarios that have been focused on only expanding the cycling infrastructure. This article introduces an innovative low-cost embedded system designed to improve cycling safety in urban areas, taking geospatial data as input. By assessing the proximity to emergency services and utilizing GPS coordinates, the system can determine the indirect current risk level for cyclists, providing real-time alerts when crossing high-risk zones. Built on a Raspberry Pi Zero board, this solution is both cost-effective and efficient, making it easily reproducible in various urban settings. Preliminary results in Porto, Portugal, showcase the system\u2019s practical application and effectiveness in enhancing cycling safety and supporting sustainable urban mobility.<\/jats:p>","DOI":"10.3390\/smartcities7040079","type":"journal-article","created":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T09:22:42Z","timestamp":1721985762000},"page":"1992-2014","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Enhancing Cycling Safety in Smart Cities: A Data-Driven Embedded Risk Alert System"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3781-7439","authenticated-orcid":false,"given":"Jos\u00e9","family":"Ferreira","sequence":"first","affiliation":[{"name":"FEUP, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3988-8476","authenticated-orcid":false,"given":"Daniel","family":"Costa","sequence":"additional","affiliation":[{"name":"FEUP, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"},{"name":"SYSTEC-ARISE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"429","DOI":"10.3390\/smartcities4020024","article-title":"IoT in Smart Cities: A Survey of Technologies, Practices and Challenges","volume":"4","author":"Syed","year":"2021","journal-title":"Smart Cities"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Samarakkody, A., Amaratunga, D., and Haigh, R. 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