Smart Traffic Management System Using IOT and Machine Learning

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dc.contributor.authorSoundarya R Raikar 1NH22CS213
dc.contributor.authorSrushti 1NH22CS218
dc.contributor.authorAbhijith U B 1NH22EC002
dc.contributor.authorAnkitha B G 1NH22EC017
dc.date.accessioned2026-02-09T08:46:53Z
dc.date.available2026-02-09T08:46:53Z
dc.date.issued2026-02-09
dc.description.abstractUrban traffic congestion continues to be one of the most critical problems in fast growing cities, leading to longer travel durations, increased fuel consumption, higher pollution levels, and daily stress for commuters. Conventional fixed cycle traffic lights are unable to respond to constantly changing road conditions, which results in poor traffic movement and frequent bottlenecks. To address these shortcomings, this project presents a smart traffic management solution that combines Internet of Things (IoT) technology, embedded hardware, machine learning (ML), and cloud computing to optimize signal control, improve safety, and reduce congestion in real time. The system collects live traffic data using IR sensors, ultrasonic sensors, and camera modules to detect vehicle count, presence, and classification.
dc.identifier.urihttp://192.168.75.5:4000/handle/123456789/20999
dc.titleSmart Traffic Management System Using IOT and Machine Learning
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