International Journal of Scientific Research and Engineering Development

Road surface conditions directly influence transportation safety, vehicle maintenance cost, and passenger comfort. Traditional road inspection methods rely on manual surveys, which are time consuming, expensive, and often inaccurate due to human error. With the increasing number of vehicles and expanding road networks, there is a need for an automated and reliable road monitoring system. This project presents a road analysis and categorization approach based on time-frequency detection techniques. The proposed system collects vibration signals generated from a moving vehicle using sensors such as accelerometers and gyroscopes. When a vehicle travels over different road surfaces such as smooth asphalt, rough road, potholes, and speed breakers, each surface produces a unique vibration signature. The recorded signals are analyzed using time-frequency signal processing methods such as Short-Time Fourier Transform and wavelet transform. These methods allow identification of both time and frequency characteristics of road vibrations. By extracting meaningful features from the signal patterns, the system categorizes the road condition automatically. The proposed approach helps detect damaged roads, uneven surfaces, and potholes in real time. The system can be integrated into smart transportation and intelligent vehicle systems for continuous road monitoring. This research demonstrates that time-frequency analysis provides an effective and low-cost solution for road quality assessment and supports safer and more efficient transportation infrastructure management.

S.Revanth Babu, Kalimi Naganika, M.Sasi Kumar, Ch.Pavani, VR.Manoj Kumar,"Categorizing Road Analysis Through Time Frequency Depection of Tyre Sensor Signals" International Journal of Scientific Research and Engineering Development, V9(2): Page(1510-1515) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.