Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | Big Data Analytics in the Social and Ubiquitous Context |
| Editors | Martin Atzmueller, Alvin Chin, Frederik Janssen, Immanuel Schweizer, Christoph Trattner |
| Place of Publication | Berlin |
| Publisher | Springer |
| Pages | 128-146 |
| Number of pages | 16 |
| ISBN (Print) | 978-3-319-29008-9 |
| DOIs | |
| Publication status | Published - 7 Jan 2016 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Verlag |
| Number | 9546 |
| Volume | 9546 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Keywords
- EWI-26650
- Anomaly Detection
- METIS-315137
- IR-98919
- Machine Learning
Cite this
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RoADS: A road pavement monitoring system for anomaly detection using smart phones. / Seraj, Fatjon; van der Zwaag, B.J.; Dilo, Arta; Luarasi, Tamara; Havinga, Paul J.M.
Big Data Analytics in the Social and Ubiquitous Context. ed. / Martin Atzmueller; Alvin Chin; Frederik Janssen; Immanuel Schweizer; Christoph Trattner. Berlin : Springer, 2016. p. 128-146 (Lecture Notes in Computer Science; Vol. 9546, No. 9546).Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review
TY - CHAP
T1 - RoADS: A road pavement monitoring system for anomaly detection using smart phones
AU - Seraj, Fatjon
AU - van der Zwaag, B.J.
AU - Dilo, Arta
AU - Luarasi, Tamara
AU - Havinga, Paul J.M.
N1 - 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers
PY - 2016/1/7
Y1 - 2016/1/7
N2 - Monitoring the road pavement is a challenging task. Authorities spend time and finances to monitor the state and quality of the road pavement. This paper investigate road surface monitoring with smartphones equipped with GPS and inertial sensors: accelerometer and gyroscope. In this study we describe the conducted experiments with data from the time domain, frequency domain and wavelet transformation, and a method to reduce the effects of speed, slopes and drifts from sensor signals. A new audiovisual data labelling technique is proposed. Our system named RoADS, implements wavelet decomposition analysis for signal processing of inertial sensor signals and Support Vector Machine (SVM) for anomaly detection and classification. Using these methods we are able to build a real time multiclass road anomaly detector. We obtained a consistent accuracy of ≈90% on detecting severe anomalies regardless of vehicle type and road location. Local road authorities and communities can benefit from this system to evaluate the state of their road network pavement in real time.
AB - Monitoring the road pavement is a challenging task. Authorities spend time and finances to monitor the state and quality of the road pavement. This paper investigate road surface monitoring with smartphones equipped with GPS and inertial sensors: accelerometer and gyroscope. In this study we describe the conducted experiments with data from the time domain, frequency domain and wavelet transformation, and a method to reduce the effects of speed, slopes and drifts from sensor signals. A new audiovisual data labelling technique is proposed. Our system named RoADS, implements wavelet decomposition analysis for signal processing of inertial sensor signals and Support Vector Machine (SVM) for anomaly detection and classification. Using these methods we are able to build a real time multiclass road anomaly detector. We obtained a consistent accuracy of ≈90% on detecting severe anomalies regardless of vehicle type and road location. Local road authorities and communities can benefit from this system to evaluate the state of their road network pavement in real time.
KW - EWI-26650
KW - Anomaly Detection
KW - METIS-315137
KW - IR-98919
KW - Machine Learning
U2 - 10.1007/978-3-319-29009-6
DO - 10.1007/978-3-319-29009-6
M3 - Chapter
SN - 978-3-319-29008-9
T3 - Lecture Notes in Computer Science
SP - 128
EP - 146
BT - Big Data Analytics in the Social and Ubiquitous Context
A2 - Atzmueller, Martin
A2 - Chin, Alvin
A2 - Janssen, Frederik
A2 - Schweizer, Immanuel
A2 - Trattner, Christoph
PB - Springer
CY - Berlin
ER -