IOT-Based Smart Traffic Management System

Using a four-lane configuration outfitted with LED traffic signals for efficient traffic control and infrared sensors for real-time vehicle density monitoring, this project showcases the creation of an intelligent traffic management system utilising Internet of Things technology. To optimise traffic flow, the Arduino Uno and Node MCU WiFi module act as the central controller units, analysing sensor data to modify the traffic lights in real-time. In order to improve road safety and efficiency, the system has a mobile application for tracking traffic density and remotely controlling the signals. Through a useful and interactive model, this creative approach shows how IoT technology may be used to address urban traffic issues

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-18
DOI
https://doi.org/10.22214/ijraset.2025.67322
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

IOT-Based Smart Traffic Management System

Nitish Kornu
International Journal for Research in Applied Science and Engineering Technology
Traffic Prediction and Management Techniques
article

IOT-Based Smart Traffic Management System

Nitish Kornu
article en

Abstract

Using a four-lane configuration outfitted with LED traffic signals for efficient traffic control and infrared sensors for real-time vehicle density monitoring, this project showcases the creation of an intelligent traffic management system utilising Internet of Things technology. To optimise traffic flow, the Arduino Uno and Node MCU WiFi module act as the central controller units, analysing sensor data to modify the traffic lights in real-time. In order to improve road safety and efficiency, the system has a mobile application for tracking traffic density and remotely controlling the signals. Through a useful and interactive model, this creative approach shows how IoT technology may be used to address urban traffic issues

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Dwarkadas J. Sanghvi College of Engineering (IN)
Openalex Percentile: Top 95%
Traffic Prediction and Management Techniques
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