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An Automatic Survey System for Paved and Unpaved Road Classification and Road Anomaly Detection using Smartphone Sensor
- Source :
- SOLI
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- For developing countries like Timor-Leste, regular road surface monitoring is a major challenge not only for maintaining road quality but also for national plan of road network construction. In Timor-Leste nearly 50% of roads are still unpaved. For this reason, an automated system is required to do a survey of paved and unpaved roads. In this study, we present a new approach for the use of smartphones sensor to classify paved and unpaved roads, and anomaly detection. Although, the most remarkable factor to differentiate paved and unpaved road is based on amplitude of the vertical acceleration, each vehicle has a different type of suspension system. Therefore, we used high-dimensional features and state-of-the-art machine learning techniques to make the system robust for differences of vehicle and also smartphone type. This study divided into two stages such as paved and unpaved road classification and road anomaly detection such as pothole and bump. For paved and unpaved road classification, we tried to use the SVM, HMM and ResNet and compared the performance of these models. Of all comparison, the ResNet was the best choice in this study, because it outperformed the SVM and HMM on the all performance evaluation criteria. Furthermore, the KNN and DTW are applied for anomaly detection on the paved road. The KNN-DTW are also compared to the other machine learning techniques like SVM and classical KNN using same criteria. As a result of the comparison, the KNN-DTW and SVM performed better than classical KNN.
- Subjects :
- business.industry
Computer science
020207 software engineering
02 engineering and technology
Machine learning
computer.software_genre
Two stages
Vertical acceleration
Support vector machine
ComputingMethodologies_PATTERNRECOGNITION
ComputerSystemsOrganization_MISCELLANEOUS
Road surface
0202 electrical engineering, electronic engineering, information engineering
Pothole
020201 artificial intelligence & image processing
Anomaly detection
Artificial intelligence
Unpaved road
business
Hidden Markov model
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)
- Accession number :
- edsair.doi...........f561adc09af374af3c9d0c16401c20d8