DESIGN AND IMPLEMENTATION OF INTELLIGENCE SYSTEM FOR POTHOLES DETECTION USING LABVIEW

Authors

  • Arivalagan M. Assistant Professor, Department of Electronics and Instrumentation Engineering, Saveetha Engineering College, Chennai, India. Author
  • Lavanya M. Assistant Professor, Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India. Author
  • Vijayanandh D. Assistant Professor, Electrical and Electronics Engineering, Hindusthan College of Engineering and Technology, Coimbatore. Author
  • Manonmani A. Assistant Professor, Department of Electronics and Instrumentation Engineering, Saveetha Engineering College, Chennai, India. Author

DOI:

https://doi.org/10.61841/fxpf5n15

Keywords:

Potential Collision, Accidents, Potholes, GPS, LabVIEW

Abstract

Vehicles are an important way of transportation all over the world. There are many cases of road accidents every day in the world. Such accidents are the main reason for traffic jams on the road, consequently resulting in a loss of valuable time. One of the main problems in developing countries is the maintenance of roads. Well-maintained roads contribute a serious portion to the country’s economy. Identification of pavement distress like potholes not only helps drivers to avoid accidents or vehicle damages. The frequency of road accidents is extremely high, which causes tons of injury to human life and valuable properties. The number of accidents is extremely high in hilly and fog-affected areas. Many road accidents are caused by a collision between vehicles due to the inability of the drivers to gauge the perimeter of their vehicles, and the other reason is unawareness of nearby vehicles. This project introduces a GPS-based system that actively and continuously sends vehicle location coordinates (latitude/longitude) to the LabVIEW, which processes/analyses data from all such vehicles, predicts potential collisions, and sends a back alert to the vehicle to raise a visual/sound alert. 

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References

[1] Zhang, Z., Ai, X., Chan, C.K., and Dahnoun, N., 2014. An efficient algorithm for pothole detection

using stereovision. In 2014, IEEE International Conference on Acoustics, Speech and Signal Processing

(ICASSP) (pp. 564-568). IEEE.

[2] Matthies, L., and Rankin, A., 2003, October. Negative obstacle detection by thermal signature. In Proceedings

2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No. 03CH37453) (Vol. 1, pp. 906-913). IEEE.

[3] Ahn, J., Wang, Y., Yu, B., Bai, F., and Krishnamachari, B., 2012, March. RISA: Distributed road information sharing architecture. In 2012 Proceedings IEEE INFOCOM (pp. 1494–1502). IEEE.

[4] Ranganathan, P., and Olson, E., 2010, October. Automated safety inspection of grade crossings. In 2010

IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2149-2154). IEEE.

[5] Mednis, A., Strazdins, G., Zviedris, R., Kanonirs, G., and Selavo, L., 2011, June. Real-time pothole detection

using Android smartphones with accelerometers. In 2011 International conference on distributed computing in

sensor systems and workshops (DCOSS) (pp. 1-6). IEEE.

[6] E. Buza S. Omanovic and A. Huseinovic: Pothole Detection with Image Processing and Spectral Clustering.

In 2nd International Conference on Information Technology and Computer Networks, Pages 48–53, 2013.

[7] K. T. Chang, J. R. Chang and J. K. Liu: Detection of Pavement Distresses Using 3D Laser Scanning

Technology, International Conference on Computing in Civil Engineering 2005

[8] Li, Q., Yao, M., Yao, X., and Xu, B. (2009): A real-time 3D Scanning System for pavement distortion

Inspection, measurement science, and technology, pages 15702-15709.

[9] K. C. P. Wang: Challenges and feasibility for comprehensive automated survey of pavement conditions, In 8th International Conference on Applications of Advanced Technologies in Transportation Engineering (2004), Pages 531-536 Z. Hou, K. C. P. Wang, and W. Gong: Experimentation of 3D pavement imaging through stereovision, In International Conference on Transportation Engineering (2007), Pages 376-381.

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Published

31.05.2020

How to Cite

M., A., M., L., D., V., & A., M. (2020). DESIGN AND IMPLEMENTATION OF INTELLIGENCE SYSTEM FOR POTHOLES DETECTION USING LABVIEW. International Journal of Psychosocial Rehabilitation, 24(3), 3695-3700. https://doi.org/10.61841/fxpf5n15