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Optimized Traffic Navigation System

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Optimized Traffic Navigation System


Archi Khandelwal



Archi Khandelwal "Optimized Traffic Navigation System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025, pp.575-579, URL: https://www.ijtsrd.com/papers/ijtsrd78594.pdf

In urban cities, traffic congestion continues to remain a serious issue resulting in to extended travel times, increased consumption of petroleum, and pollution of the surrounding environment. Traditional traffic management systems rely on pre-set routes and static signal arrangements, therefore insufficient to dynamically adjust to changing conditions. This project leverages AI (Artificial Intelligence), Machine learning and IOT (Internet of Things) in order to improve traffic flow and urban mobility. So as to obtain real-time traffic data, the system integrates GPS trackers, AI-driven cameras and IoT-enabled sensors. Algorithms developed using machine learning are implemented to process this data in order to improve route recommendations and identify patterns of congestion. In order for better vehicle flow, smart traffic signal management additionally serves to adjust signal timings. Incident detection and management will be done using AI-driven object detection. The system architecture is designed using MySQL, Python with Flask, and React.js for the frontend. Tensor Flow and Scikit-learn are tools for predictive analytics, while Apache Kafka handles real-time data streaming. MQTT integration allows interaction among IoT devices and the central processing unit. This enables for timely rerouting and emergency response. The system's objective is to increase commuter safety, minimize emissions, and reduce congestion by dynamically optimizing traffic signals and routes.

Traffic Prediction, Artificial Intelligence, Internet of Things, machine learning, Python flask, Traffic management, incident detection, deep learning.


IJTSRD78594
Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025
575-579
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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