A New Measure for Analysing Accelerometer Data towards Developing Efficient Road Defect Profiling Systems
H. Bello-Salau, A. M. Aibinu, E. N. Onwuka, J. J. Dukiya, M. E. Bima, A. J. Onumanyi, T. A. Folorunso
Journal of Scientific Research and Reports · pp. 108–116 · Published 27 Apr 2015
10.9734/JSRR/2015/16840Abstract
Aims: In this paper, we propose a new measure for analysing data obtained from an accelerometer with the aim of improving road surface condition monitoring and defect detection systems. Study Design: The study consisted of an experimental setup involving the use of an accelerometer embedded device connected to a laptop, all mounted in a vehicle for data acquisition and storage. Place and Duration of Study: Data gathering was conducted within the campus of the Federal University of Technology, Minna, for a period of two months. Methodology: The accelerometer was programmed to capture vibration signals along the x, y and z-axis with special interest in the z-axis because it monitors the up/down motion of the vehicle. Our algorithm uses what we call the “z-difference square” measure to analyse raw accelerometer data towards improving road defect detection. LABVIEW was used to configure the accelerometer device, while the algorithm for post data processing and statistical analyses were implemented in MATLAB. Results: Inferences drawn from the raw data and other statistical measures indicate that the proposed measure provides the advantage of using single threshold values for detection, inherent averaging, and potential for spatial localization of potholes, as compared to other statistical measures. Conclusion: The use of our proposed “z-difference square” measure for analysing accelerometer data will provide a simple yet efficient and effective statistical measure for improving road defect detection systems.
Cited by 21
A. A. Babatunde, Gbola. K. Adewuyi, M. A. Oyekola · Journal of Geography Environment and Earth Science International · 2019
Nuno Silva, Vaibhav Shah, J. Soares · Italian National Conference on Sensors · 2018
H. Bello-Salau, A. Aibinu, A. Onumanyi · 2018
J. Soares, Nuno Silva, Vaibhav Shah · 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · 2018
H. Bello-Salau, A. Aibinu, E. Onwuka · 2016
H. Bello-Salau, A. Onumanyi, D. Michael · 2021
Nuno Silva, J. Soares, Vaibhav Shah · CENTERIS/ProjMAN/HCist · 2017
Giacomo Alessandroni · 2016
Relebogile Makhulu Langa, Michael Nthabiseng Moeti, Senota Frans Kgoete · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2024
H. Bello-Salau, A.M. Aibinu, Z. Wang · Engineering Science and Technology, an International Journal · 2019
Related research
- Evaluating Existing Mobile Apps for Toddler Parenting: Recommendations for Future App Developers — shares topic coverage
- Correlation between Anxiety and Smartphone Addiction in the Teenager Population at Kalam Kudus II Senior High School — shares topic coverage
- Automated Fish Feeder Using Scheduler Mobile Application — shares topic coverage
- Evaluation of Evidence Based Medicine Knowledge and Skills among a Sample of Medical Students in King Abdul Aziz University: A Follow up Study — shares topic coverage
- Smart Fuel Monitoring for Agricultural Fleet Operations Using Tilt Sensors and Cloud Data Processing — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
21
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.