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Smart City Traffic Management
Aug 2024 - Oct 2024

Smart City Traffic Management

IoT & AI based adaptive traffic control

01. The Challenge

Static traffic timers cause unnecessary congestion.

02. The Solution

Developed an adaptive system using camera feeds to adjust signal timings in real-time.


Overview

Urban congestion is a major issue. This project utilizes existing CCTV infrastructure to count vehicles and optimize traffic light timings dynamically.


System Design

Edge devices (Raspberry Pi/Jetson Nano) process video feeds locally to count vehicles. This data is sent via MQTT to a central server which calculates optimal green light durations using a weighted algorithm.


System Architecture

YOLO for vehicle counting
Edge devices for processing
Cloud dashboard for analytics

Project Links

Technologies

PythonYOLOMQTTAWS IoT

Key Impact

Reduced wait times by 30%
Lowered emissions
Real-time analytics