{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:11:02Z","timestamp":1780053062715,"version":"3.54.0"},"reference-count":45,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,4]],"date-time":"2026-01-04T00:00:00Z","timestamp":1767484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2019 China Ministry of Education University-Industry Collaborative Education Program"},{"name":"Datang Mobile Communication Equipment Co., Ltd.","award":["201902094001"],"award-info":[{"award-number":["201902094001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Traffic violations and road accidents remain significant challenges in developing safe and efficient transportation systems. Despite technological advancements, improving vehicle detection accuracy and enabling real-time traffic management remain critical research priorities. This study proposes YOLO-LIO, an enhanced vehicle detection framework designed to address these challenges by improving small-object detection and optimizing real-time deployment. The system introduces multi-scale detection, virtual zone filtering, and efficient preprocessing techniques, including grayscale transformation, Laplacian variance calculation, and median filtering to reduce computational complexity while maintaining high performance. YOLO-LIO was rigorously evaluated on five datasets, GRAM Road-Traffic Monitoring (99.55% accuracy), MAVD-Traffic (99.02%), UA-DETRAC (65.14%), KITTI (94.21%), and an Author Dataset (99.45%), consistently demonstrating superior detection capabilities across diverse traffic scenarios. Additional system features include vehicle counting using a dual-line detection strategy within a virtual zone and speed detection based on frame displacement and camera calibration. These enhancements enable the system to monitor traffic flow and vehicle speeds with high accuracy. YOLO-LIO was successfully deployed on Jetson Nano, a compact, energy-efficient hardware platform, proving its suitability for real-time, low-power embedded applications. The proposed system offers an accurate, scalable, and computationally efficient solution, advancing intelligent transportation systems and improving traffic safety management.<\/jats:p>","DOI":"10.3390\/a19010042","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T12:38:56Z","timestamp":1767616736000},"page":"42","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["YOLO-LIO: A Real-Time Enhanced Detection and Integrated Traffic Monitoring System for Road Vehicles"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5217-4999","authenticated-orcid":false,"given":"Rachmat","family":"Muwardi","sequence":"first","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100811, China"},{"name":"Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063012, China"},{"name":"Department of Electrical Engineering, Universitas Mercu Buana, Jakarta 11650, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2382-0509","authenticated-orcid":false,"given":"Haiyang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100811, China"},{"name":"Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongmin","family":"Gao","sequence":"additional","affiliation":[{"name":"Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7569-1772","authenticated-orcid":false,"given":"Mirna","family":"Yunita","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100811, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7908-9065","authenticated-orcid":false,"given":"Rizky","family":"Rahmatullah","sequence":"additional","affiliation":[{"name":"Research Center for Telecommunication, National Research and Innovation Agency (BRIN), Jawa Barat 40132, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8832-9219","authenticated-orcid":false,"given":"Ahmad","family":"Musyafa","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universitas Pamulang, South Tangerang 15417, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Galang Persada Nurani","family":"Hakim","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universitas Mercu Buana, Jakarta 11650, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9835-5453","authenticated-orcid":false,"given":"Dedik","family":"Romahadi","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Universitas Mercu Buana, Jakarta 11650, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Nigam, N., Singh, D.P., and Choudhary, J. 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