AN OVERVIEW OF ROAD HEALTH MONITORING SYSTEM FOR RIGID PAVEMENT BY TERRESTRIAL LASER SCANNER
- Dept. of Computer Science& Engineering, Rajiv Gandhi Institute of Petroleum Technology Jais, Amethi, Uttar Pradesh, India
Keywords: Road health monitoring, Road management, SHM, Terrestrial laser scanners (TLS), Accelerometer, sensor
Abstract. Structural health monitoring (SHM) applications for roads should be created in order to save finances, protect public safety, and provide long-lasting road infrastructure. The terrestrial laser scanner (TLS) will be employed in this project for collecting data, used for monitoring purposes. LiDAR camera mounted on moving vehicle generating 3D point cloud is used for monitoring purpose. Poorly maintained roads result in lower productivity, higher fuel consumption, increased mechanical wear, hazardous operating conditions, driver discomfort, and higher rolling resistances. Road management agencies suffer with pavement repair methods and the finances to keep the existing road networks in good working order. The goal of this research work is to create a low-cost smart road health monitoring system that uses camera-based monitoring and smart phone sensors to identify the road section for maintenance. We have discovered that using accelerometers for pothole detection is ideal for this application. The road patches or pot holes for 2 km area of the RGIPT campus using accelerometer is being done. The smart phone will upload the position and any kind of undulated road surface to the cloud when the vehicle passes over it. Use of accelerometer may detect internal damage of the pavements before it appears on the top surface of the road. When other vehicles move towards an irregular road surface, the cloud will issue an undulated road surface reminder to make sure that the vehicle may safely and smoothly drive through the area. The system is simply dependent on a single phone setting and uses raw accelerometer measurements, which can record irregular driving or quick brakes. The data in this system are collected from the mobile phone and sensor for monitoring and forecasting of road surface. So, every pavement defect has different classification and treatment approach, as well as severity levels.