Accident and Traffic Prediction and Management Methods for Smart City: an Overview

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Dastbaz Forouzan; Chalechale Abdolah

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2024 | Issue:10

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Title

Accident and Traffic Prediction and Management Methods for Smart City: an Overview

Author(s)

Dastbaz Forouzan | Chalechale Abdolah

Keywords

Traffic detection

Accident prediction

Deep learning

Image processing

Smart city

Internet of Things

Abstract

Nowadays, in many developing countries, the surge in urbanization and vehicle congestion has led to a rise in traffic density and city accidents. This research aims to explore and compare various advanced Traffic detection methods, Accident prediction in smart cities using Image processing, Deep learning algorithms, and Internet of Things (IoT) technologies. These technologies include infrared sensors and video image processors installed on roads, and Accident prediction systems. The goal is to alleviate traffic congestion, enhance vehicle flow, and decrease accidents. The study concludes with a comparison of the reviewed algorithms’,accuracy and speed in Traffic detection and Accident prediction.

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APA: Copy

Dastbaz, Forouzan, & Chalechale, Abdolah. (2024). Accident and Traffic Prediction and Management Methods for Smart City: an Overview. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147660/en

Vancouver: Copy

Dastbaz Forouzan, Chalechale Abdolah. Accident and Traffic Prediction and Management Methods for Smart City: an Overview. 2024. Available from: https://sid.ir/paper/1147660/en

IEEE: Copy

Forouzan Dastbaz, and Abdolah Chalechale, “Accident and Traffic Prediction and Management Methods for Smart City: an Overview,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147660/en

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