Overview

Welcome to the AI-Powered Accident Detection and Real-Time Monitoring System with Python & Computer Vision! In this hands-on course, you'll learn how to develop a real-time accident detection and alert system using deep learning, IoT, and mobile application technologies. This course covers everything from data preprocessing and model validation to real-time inference, communication protocols, and mobile app integration.What You'll Learn:• Set up your AI development environment with Google Colab, TensorFlow, OpenCV, and essential deep-learning libraries.• Preprocess accident detection data by applying image normalization and resizing using Convolutional Neural Networks (CNNs) for improved accuracy.• Train and validate your accident detection model with classification metrics, recall, and precision to ensure reliability.• Implement real-time inference in VS Code to detect accidents in live video feeds.• Use MQTT protocol for seamless communication between IoT devices, servers, and mobile applications for instant alert notifications.• Build a mobile application with React (frontend) and Flask (backend) to display live video streams and detection results.• Handle real-world challenges such as false positives, low-light conditions, and various accident scenarios to enhance detection accuracy.• Deploy the system for smart city applications, traffic monitoring, and intelligent transportation systems to improve road safety.Enroll today and start building your AI-Powered Accident Detection and Real-Time Monitoring & Alert

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