Paper Title
A SMART TRAFFIC MANAGEMENT SYSTEM USING REAL-TIME COMPUTER VISION, VEHICLE TRACKING, AND BLOCKCHAIN-BASED ADAPTIVE SIGNAL CONTROLS

Abstract
As more residents are added to cities and commu nities, cars have become a greater source of congestion than they used to be. Urbanization is leading to a greater number of cars on the road, and therefore, a greater number of people needing to use public transportation or other alternative means. With increasing numbers of cars on the road and increasingly congested streets, cities and communities must find a way to reduce the time that drivers and pedestrians spend in congested areas and waiting for emergency vehicles. Currently, effective approaches to traffic signal control are hindering improvements in traffic movement as well as improving the responsiveness of emer gency vehicles. However, through the use of Deep Learning and Decentralized Technologies, there have been significant recent advancements toward implementing intelligent, adaptive traffic control; therefore, the following study will propose an Integrated Smart Traffic Management System (STMS), which provides the system to control vehicle movements by employing the utilization of real-time vehicle detection (using models developed based on YOLO [1][2]), multi-object tracking (using DeepSORT [3]), speed estimation (using [4]), recognizing emergency vehicles (using [5]), analyzing congestion (using the heatmap [6]), and he use of a Blockchain to manage the signal rule set and rule management (using Ethereum smart contracts [7][8][9]), creating an effective and practical form of traffic signal management, which uses the Ethereum contract as a means of ensuring a tamper-proof storage of adaptive signal parameters; thus eliminating the vulnerability to central control systems [10][11]. The study also demonstrated through experimental evaluation of the effectiveness of the proposed STMS framework in the area of traffic surveillance, providing reliable detection of vehicles, continuously tracking vehicles, accurately estimating the level of congestion, and successfully identifying emergency vehicles. The integration of utilizing Blockchain to manage the traffic signal rules will add an additional layer of transparency and security to Integrated Transportation Systems (ITS) as compared to traditional ITS methods [7][10][11]. This STMS framework will serve as a scalable solution to support the smart city model, thus allowing the implementation of increased efficiencies in traffic flow, thereby reducing delays in traffic movement and improving the response times of emergency vehicles. Keywords - Computer Vision, YOLO, DeepSORT, Traffic Surveillance, Smart City, Blockchain, Ethereum, Smart Con tracts, Speed Estimation, Emergency Vehicle Detection, Adaptive Traffic Signals, Congestion Analysis, Intelligent Transportation Systems (ITS), Real-Time Video Analytics, Decentralized Rule Management.