Review of IoT-Based Traffic Management Systems: Advancements in Image Processing for Smart Transportation

This paper introduces a survey on IoT-based systems designed to collect, process, and store real-time traffic data from collector roads and closed campuses. By integrating image processing techniques with IoT capabilities, the research article aims to highlight optimization strategies for smooth traffic flow, congestion alleviation, and improvement of urban mobility. The system's key features discussed in different research articles include dynamic traffic updates displayed on roadside message units, intelligent traffic signal adjustments based on current conditions, and prioritization to emergency vehicles for seamless movement. The implementation of multiple proposed systems by various authors has successfully managed to enhance traffic efficiency, reduce fuel consumption, and lower emissions, thereby contributing to a more sustainable and liveable urban environment.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/eaic66483.2025.11101541
Citations
6
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
6.04
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article

Review of IoT-Based Traffic Management Systems: Advancements in Image Processing for Smart Transportation

Dharminder Chauhan, Rohit Kumar Singh, Swati Sharma, Shivam Chauhan et al.
6 citations
Traffic Prediction and Management Techniques
6.04
article

Review of IoT-Based Traffic Management Systems: Advancements in Image Processing for Smart Transportation

Dharminder Chauhan, Rohit Kumar Singh, Swati Sharma, Shivam Chauhan, Nipun Tyagi, Swapnil Srivastava
article en
6 citations

Abstract

This paper introduces a survey on IoT-based systems designed to collect, process, and store real-time traffic data from collector roads and closed campuses. By integrating image processing techniques with IoT capabilities, the research article aims to highlight optimization strategies for smooth traffic flow, congestion alleviation, and improvement of urban mobility. The system's key features discussed in different research articles include dynamic traffic updates displayed on roadside message units, intelligent traffic signal adjustments based on current conditions, and prioritization to emergency vehicles for seamless movement. The implementation of multiple proposed systems by various authors has successfully managed to enhance traffic efficiency, reduce fuel consumption, and lower emissions, thereby contributing to a more sustainable and liveable urban environment.

Chaudhary Charan Singh University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Traffic Prediction and Management Techniques
6.04
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Review of IoT-Based Traffic Management Systems: Advancements in Image Processing for Smart Transportation — Dharminder Chauhan, Rohit Kumar Singh, et al. · (2025) | TGRS Research Map | TGRS