An intelligent road condition monitoring system using vibration sensors and ESP32
Students Name: Yuzvak Ihor Vasylovych
Qualification Level: magister
Speciality: Information Technology Design
Institute: Institute of Computer Science and Information Technologies
Mode of Study: full
Academic Year: 2024-2025 н.р.
Language of Defence: ukrainian
Abstract: Yuzvak I.V., Korpylyov D.V. (leader). Intelligent road condition monitoring system using vibration sensors and ESP32. Master’s thesis - Lviv Polytechnic National University, Lviv, 2024. Extended annotation. The purpose of the thesis is to develop an intelligent road condition monitoring system based on the use of vibration sensors and an ESP32 microcontroller, which will allow automating the process of collecting and analyzing data on the condition of the road surface. The system should provide: • collection of vibration data during the movement of vehicles to detect road damage, such as potholes, cracks or other defects; • processing of the collected data using algorithms to detect vibration anomalies indicating deterioration of the pavement; • transmission of the analyzed information to a remote server via wireless networks for centralized storage and further analysis; • creation of a road condition map to ensure prompt response to identified problems; • reduction of costs for maintenance and repair of the road surface through early detection of damage and planning of repair work based on the data received. Additionally, the system can be expanded to monitor other road condition parameters, such as wear levels or changes in pavement structure, which will provide a comprehensive assessment of road infrastructure. The main goal is to detect potholes and road damage in real time. This will provide an effective system for monitoring and preventive road repairs through remote access to data obtained from vibration sensors. The system will be useful for municipal services and transport companies that need to regularly monitor the road surface. Research objectives To develop the hardware part of the system that will provide data collection from vibration sensors. To create and implement algorithms for analyzing the obtained data to identify vibration anomalies indicating the presence of holes, cracks or other damage to the road surface. To integrate a wireless data transmission module via Wi-Fi to send the analyzed information to remote servers for centralized storage and further analysis. To test the developed system in real conditions in order to determine its accuracy, efficiency and suitability for monitoring the condition of roads. To investigate the possibility of expanding the functionality of the system to monitor other road surface parameters, such as wear level, structural changes or other characteristics. The scientific novelty of the master’s thesis "Intelligent road condition monitoring system using vibration sensors and ESP32" lies in the development of new methods and approaches to automated road surface monitoring using modern IoT technologies. The main aspects of the novelty include: Integration of vibration sensors with the ESP32 platform. A new system for collecting data on the vibration characteristics of the road surface using sensors and the ESP32 microcontroller has been developed. This platform provides high efficiency of data transmission via Wi-Fi or other wireless communication protocols. Automatic detection of vibration anomalies. A new approach is proposed to automatically detect road surface damage (potholes, cracks) using vibration data analysis. This allows for timely detection of problem areas without the need for manual inspection. Remote monitoring and real-time data analysis. The system uses IoT for remote monitoring of road conditions in real time, which allows for prompt response to damage and transmission of data to relevant authorities for making decisions about repairs. Application of machine learning algorithms. New vibration data analysis algorithms have been implemented that are trained on historical data to better predict the condition of the road surface. This aspect allows for improved prediction accuracy and speed of response to problems. Energy efficiency and scalability. Thanks to the use of ESP32, the proposed system is energy efficient and easily scalable for various types of roads, from city streets to highways, without significantly increasing the cost of implementation. Thus, the work makes an important contribution to the field of intelligent infrastructure monitoring and suggests new approaches to improving the efficiency of road maintenance with minimal maintenance and repair costs. The thesis contains: 102 articles, __ fig., _ table, 85 references to the used sources. Keywords: intelligent system, road monitoring, vibration sensors, ESP32, АNТ-801S vibration sensor, GPS, road surface, pothole detection, vibration anomalies, data collection, data transfer, Wi-Fi, road condition analysis, repair optimization, system testing. List of used literature sources: 1. Strutu, M.; Stamatescu, G.; Popescu, D. A mobile sensor network based road surface monitoring system. In Proceedings of the 2013 17th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, 11–13 October 2013; pp. 630–634. 2. Buza, E.; Omanovic, S.; Huseinovic, A. Pothole detection with image processing and spectral clustering. In Proceedings of the 2nd International Conference on Information Technology and Computer Networks, Athens, Greece, 27–28 April 2013; pp. 48–53. 3. Kelvin, C. Automated Pavement Distress Survey through Stereovision; Technical Report of Highway IDEA Project; National Academy of Sciences: Washington, DC, USA, 2004. 4. Vijay, S.; Arya, K. Low Cost—FPGA Based System for Pothole Detection on Indian Roads. Master’s Thesis, Indian Institute of Technology Bombay, Mumbai, India, 2006. 5. Salari, E.; Chou, E.; Lynch, J.J. Pavement Distress Evaluation Using 3d Depth Information from Stereo Vision; Technical Report; The University of Toledo: Toledo, OH, USA, 2012 6. Moazzam, I.; Kamal, K.; Mathavan, S.; Usman, S.; Rahman, M. Metrology and visualization of potholes using the microsoft kinect sensor. In Proceedings of the 2013 16th International IEEE Conference on Intelligent Transportation Systems-(ITSC), The Hague, The Netherlands, 6–9 October 2013; pp. 1284–1291. 7. Hou, Z.; Wang, K.C.; Gong, W. Experimentation of 3D pavement imaging through stereovision. In Proceedings of the International Conference on Transportation Engineering 2007, Chengdu, China, 22–24 July 2007; pp. 376–381. 8. Kim, T.; Ryu, S.K. Review and analysis of pothole detection methods. J. Emerg. Trends Comput. Inf. Sci. 2014, 5, 603–608 9. Wang, H.W.; Chen, C.H.; Cheng, D.Y.; Lin, C.H.; Lo, C.C. A real-time pothole detection approach for intelligent transportation system. Math. Probl. Eng. 2015, 2015, 869627 10.Yan, W.Y.; Shaker, A.; El-Ashmawy, N. Urban land cover classification using airborne LiDAR data: A review. Remote Sens. Environ. 2015, 158, 295–310. 11.Yan, W.Y.; Yuan, X.X. A low-cost video-based pavement distress screening system for low-volume roads. J. Intell. Transp. Syst. 2018, 22, 376–389. 12.Canny, J. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 1986, PAMI-8, 697–698 13.Koch, C.; Jog, G.; Brilakis, I. Pothole detection with image processing and spectral clustering. J. Comput. Civ. Eng. 2013, 27, 370–378. 14.Jog, G.; Koch, C.; Golparvar-Fard, M.; Brilakis, I. Pothole properties measurement through visual 2D recognition and 3D reconstruction. In Proceedings of the 2012 ASCE International Workshop on Computing in Civil Engineering, Clearwater, FL, USA, 17–20 June 2012; pp. 553–560. 15.Huidrom, L.; Das, L.K.; Sud, S. Method for automated assessment of potholes, cracks and patches from road surface video clips. Procedia Soc. Behav. Sci. 2013, 104, 312–321. 16.Lokeshwor, H.; Das, L.K.; Goel, S. Robust method for automated segmentation of frames with/without distress from road surface video clips. J. Transp. Eng. 2013, 140, 31–41.