Smart Pothole Monitor

This is a Flask-based web application for analyzing road surface conditions using IMU (Inertial Measurement Unit) sensor data combined with GPS coordinates and OSRM (Open Source Routing Machine) map matching. Core Functionality: 1. Road Roughness Index (RRI) Calculation Uses the LPC/PPE (Linear Predictive Coding / Predictive Power Error) algorithm that Processes accelerometer data (ax, ay, az) to detect road surface anomalies like potholes and rough patches 2. GPS Map Matching via OSRM Snaps raw GPS coordinates to actual road geometry using a local OSRM Docker server Improves accuracy by aligning detected events to real road positions 3. Road Quality Classification Categorizes road conditions into 7 levels: Very Smooth, Smooth, Slightly Uneven, Moderate, Rough, Very Rough, Severe Each level has associated color coding for visualization