Identification of Road Distresses and Traffic Condition Through Smartphone

Abedin, Tanvir; Rahman, Kazi Mashukur; Sinan, Ahmad Qutub Ul Alam; Forhad, Farah Binte

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dc.contributor.author	Abedin, Tanvir
dc.contributor.author	Rahman, Kazi Mashukur
dc.contributor.author	Sinan, Ahmad Qutub Ul Alam
dc.contributor.author	Forhad, Farah Binte
dc.date.accessioned	2022-12-15T09:29:06Z
dc.date.available	2022-12-15T09:29:06Z
dc.date.issued	2022-05-30
dc.identifier.citation	Aleadelat, W., Ksaibati, K., Wright, C. H. G., & Saha, P. (2018). Evaluation of pavement roughness using an android-based smartphone. Journal of Stomatology, 144(3). https://doi.org/10.1061/JPEODX.0000058 Bills, T., Bryant, R., & Bryant, A. W. (2014). Towards a frugal framework for monitoring road quality. In 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 (pp. 3022–3027). https://doi.org/10.1109/ITSC.2014.6958175 Huda, C., Tolle, H., & Utaminingrum, F. (2020). Road Damaged Analysis (RODA) using Built-in Accelerometer Sensor in Smartphone. Journal of Information Technology and Computer Science, 5(2), 138–150. https://doi.org/10.25126/jitecs.202052168 ITF. (2021). Road Safety in Cities: Street Design and Traffic Management Solutions. International Transport Forum Policy Papers, 99. Janani, L., Sunitha, V., & Mathew, S. (2021). Influence of surface distresses on smartphone-based pavement roughness evaluation. International Journal of Pavement Engineering, 22(13), 1637–1650. https://doi.org/10.1080/10298436.2020.1714045 Kondiparthi, M. (2013). Three-dimensional profiling using a still shot. Journal of Micro/Nanolithography, MEMS, and MOEMS, 13(01), 1. https://doi.org/10.1117/1.jmm.13.1.011106 Li, X., & Goldberg, D. W. (2018). Toward a mobile crowdsensing system for road surface assessment. Computers, Environment and Urban Systems, 69(October 2017), 51–62. https://doi.org/10.1016/j.compenvurbsys.2017.12.005 Mandapalli, J. K., Gorthi, S. S., Gorthi, R. S., & Gorthi, S. (2019). Circular fringe projection method for 3D profiling of high dynamic range objects. VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 5(Visigrapp), 849–856. 50 https://doi.org/10.5220/0007389608490856 Rouaud, M. (2013). Probability, statistics and estimation. Propagation of Uncertainties, 191. http://www.incertitudes.fr/book.pdf Srishyla K, D. K. (2021). IRJET- Road Pavement Distress Identification and Classification using Deep Learning. Irjet, 8(6), 3384–3390. Staniek, M. (2021). Road pavement condition diagnostics using smartphone-based data crowdsourcing in smart cities. Journal of Traffic and Transportation Engineering (English Edition), 8(4), 554–567. https://doi.org/10.1016/j.jtte.2020.09.004 Thiandee, P., Witchayangkoon, B., Sirimontree, S., & Lertworawanich, P. (2019). AN EXPERIMENT ON MEASUREMENT OF PAVEMENT ROUGHNESS VIA ANDROID-BASED SMARTPHONES. https://doi.org/10.14456/ITJEMAST.2019.114 Uddin Mohammed, J., Iqbal Faheem, M., Minhajuddin Aquil, M., Scholar, P., & Principal, V. (2015). Pavement Performance Measures Using Android-Based Smart Phone Application. In Research & Indu. Appls. (IJERIA (Vol. 8, Issue III). Uzaktan, T., Dergisi, C. B. S., Kullanarak, İ. H. A., & Bozukluk, Y. (2020). Turkish Journal of Remote Sensing and GIS. 1(March), 61–77. Yeganeh, S. F., Mahmoudzadeh, A., Azizpour, M. A., & Golroo, A. (2019). Validation of smartphone based pavement roughness measures. 1–9. http://arxiv.org/abs/1902.10699	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/1616
dc.description	Supervised by Dr. Nazmus Sakib, Assistant Professor, Department of Civil and Environmental Engineering (CEE), Islamic University of Technology (IUT), Board Bazar, Gazipur, Bangladesh. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Civil and Environmental Engineering, 2022.	en_US
dc.description.abstract	One of the most serious issues in developing countries is road maintenance. Every year thousands of people lose life due to the failure in road maintenance. Road damage causes severe issues for drivers such as trip efficiency, car value, and even driving safety. In some circumstances, road degradation causes accidents that result in death. Currently, road damage detection research is expanding and presenting new ways such as the use of an accelerometer sensor. However, because of the inability to function in real-time and bad implementation, the implementations suffer from a lack of precision. Well-maintained roadways contribute significantly to the country's economy. Identification of road distress, such as potholes and bumps, assists drivers in avoiding accidents and vehicle damage, as well as assisting authorities in road maintenance. A cost-effective technique with an appropriate level of accuracy and the least amount of labor is always ideal for road distress assessment study. And smartphones give all of these via various types of sensors. The purpose of this study is to investigate the usage of smartphone apps to assess the discomfort of the road body, which directly reflects the road condition. The study investigates the source of vehicle trouble on the road. The research and observations obtained by the suggested approach for road condition evaluation were compared with a set of road infrastructure data collected by smartphone application employing sensors such as gyroscope, accelerometer, GPS, and so	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Civil and Environmental Engineering (CEE), Islamic University of Technology(IUT)	en_US
dc.subject	Potholes, Bumps, Smartphone apps, Geometric Condition, Traffic Condition, 3-axis Accelerometer Sensor	en_US
dc.title	Identification of Road Distresses and Traffic Condition Through Smartphone	en_US
dc.type	Thesis	en_US