Pothole Detection System using Machine Learning on Android Circuit Diagram This project focuses on developing a Real-Time Pothole Detection System that identifies potholes on roads using a combination of OpenCV, a custom ML model along with YOLOv8, and NodeMCU for real-time processing. The system detects potholes from video streams captured by an ESP32-CAM and triggers voice alerts to notify drivers.
The development of automated pothole detection systems has made it possible to detect potholes faster, enabling timely repairs and minimizing the cost of road maintenance. Features of pothole detection with AI. AI-based pothole detection application involves the use of multiple cameras to capture the road surface.
SumitSonar/Realtime Circuit Diagram
AI-based pothole detection systems have a number of advantages over traditional methods of pothole detection. They are: More Accurate: AI-based systems can detect potholes more accurately than a manual inspection or visual surveys. This is because AI systems can analyze large amounts of data and identify patterns that humans may not be able to see. Integrated real-time data analytics for optimized public transport, innovative road monitoring using demand prediction, and conditioning tech for sustainability, real time pothole detection either by image or video, smart parking count system for efficiency using AI/ML.
In rock identification systems: a comprehensive review [] proposed a rock detection system using hardware components and cloud-based storage.The system uses an ATmega328P micro-controller, an HC-SR04 ultrasonic sensor for telemetry and a NEO 6 m GPS module for location coordinates The HC-05 Bluetooth module is used to transfer data from the micro-controller to the Android application.
Pothole Detection Circuit Diagram
Now, we'll create a different program for live pothole detection in a video. This program can also be used with a live camera to detect potholes on the road in real-time . This program closely resembles the previous one, but here, we'll use the ' cv2.VideoCapture() ' function to capture video frames and a while loop to process them Abstract: The goal of this project endeavours to enhance road safety through a machine learning-based pothole detection system. The primary objective is to develop an artificial intelligence solution that can accurately identify and analyse potholes on road surfaces, thereby contributing to proactive road maintenance and accident prevention. This project introduces an AI-based pothole detection system using YOLOv8, high-resolution cameras, and GPS to detect and measure potholes in real-time. It provides data to authorities for quick repairs, enhancing road safety. Resources. Readme Activity. Stars. 0 stars. Watchers. 1 watching. Forks. 0 forks.
