Road Damaged Analysis (RODA) using Built-in Accelerometer Sensor in Smartphone


  • Choirul Huda Brawijaya University
  • Herman Tolle Brawijaya University
  • Fitri Utaminingrum Brawijaya University



Road damage produces serious problems for the driver such as travel efficiency, vehicle value, and even driver safety. In some cases, road damage causes accidents and ends in death. Currently, road damage detection research extends to grow and present various approaches such as the implementation of an accelerometer sensor. However, the implementations face lacks of accuracy since unable to work in real-time and poor implementation. In the end, the system inadequate to identify damaged roads effectively. Therefore, a comprehensive study was proposed. Firstly, data collection is conducted by applying a low-pass filter to obtain accurate data. The next step is estimating the range value of the accelerometer graph. In the final step, the classification is performed to identify road conditions into smooth, medium and poor. Based on some experiments that have been done, the proposed method accurately recognizes road conditions by 86.67%.


A. Alfarrarjeh, D. Trivedi, S. H. Kim, and C. Shahabi, “A Deep Learning Approach for Road Damage Detection from Smartphone Images,†Proc. - 2018 IEEE Int. Conf. Big Data, Big Data 2018, pp. 5201–5204, (2019).

Unknown, “Study: Pothole Damage Costs U.S. Drivers $3B a Year,†Insurance Journal, (2016).

A. Dhillon, “‘More deadly than terrorism’: potholes responsible for killing 10 people a day in India,

M. Triraharjo, “Tewaskan Pengendara Sepeda Motor, Jalan Berlubang Dipasang Palang Kayu,†Radar Jombang - Jawapos, Jombang, (2019).

S. Soehodho, “Public transportation development and traffic accident prevention in Indonesia,†IATSS Res., vol. 40, no. 2, pp. 76–80, (2017).

Y. Jo and S. Ryu, “Pothole detection system using a black-box camera,†Sensors (Switzerland), vol. 15, no. 11, pp. 29316–29331, (2015).

L. Ale, N. Zhang, and L. Li, “Road Damage Detection Using RetinaNet,†Proc. - 2018 IEEE Int. Conf. Big Data, Big Data 2018, pp. 5197–5200, (2019).

H. Maeda, Y. Sekimoto, T. Seto, T. Kashiyama, and H. Omata, “Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images,†Comput. Civ. Infrastruct. Eng., vol. 33, no. 12, pp. 1127–1141, (2018).

L. Zhang, F. Yang, Y. Daniel Zhang, and Y. J. Zhu, “Road crack detection using deep convolutional neural network,†Proc. - Int. Conf. Image Process. ICIP, vol. 2016-Augus, pp. 3708–3712, (2016).

B. Y. Amirgaliyev, K. K. Kuatov, and Z. Y. Baibatyr, “Road condition analysis using 3-axis accelerometer and GPS sensors,†Appl. Inf. Commun. Technol. AICT 2016 - Conf. Proc., pp. 1–5, (2017).

M. R. Carlos, M. E. Aragon, L. C. Gonzalez, H. J. Escalante, and F. Martinez, “Evaluation of detection approaches for road anomalies based on accelerometer readings-Addressing who’s who,†IEEE Trans. Intell. Transp. Syst., vol. 19, no. 10, pp. 3334–3343, (2018).

Android Developer, “Motion Sensors,†Documentation for app developers, 2019. [Online]. Available: [Accessed: 11-Jan-2020].

H. Tolle and K. Arai, “Design of Head Movement Controller System (HEMOCS) for Control Mobile Application through Head Pose Movement Detection,†Int. J. Interact. Mob. Technol., vol. 10, no. 3, pp. 24–28, (2016).

F. Al Huda, H. Tolle, and R. Andrie Asmara, “Realtime Online Daily Living Activity Recognition Using Head-Mounted Display,†Int. J. Interact. Mob. Technol., vol. 11, no. 3, p. 67, (2017).

B. Guksa and B. Erkmen, “Smart Phone Application for Drowsiness Detection during Driving,†Int. Conf. Front. Sensors Technol., pp. 218–221, (2017).

A. Allouch, A. Koubaa, T. Abbes, and A. Ammar, “RoadSense: Smartphone Application to Estimate Road Conditions Using Accelerometer and Gyroscope,†IEEE Sens. J., vol. 17, no. 13, pp. 4231–4238, (2017).

L. B. Gueta and A. Sato, “Classifying road surface conditions using vibration signals,†Proc. - 9th Asia-Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. APSIPA ASC 2017, vol. 2018-Febru, no. December, pp. 39–43, (2018).

Developer Android, “Measure app performance with Android Profiler,†2020. [Online]. Available: [Accessed: 08-Apr-2020].

P. M. Harikrishnan and V. P. Gopi, “Vehicle Vibration Signal Processing for Road Surface Monitoring,†IEEE Sens. J., vol. 17, no. 16, pp. 5192–5197, (2017).




How to Cite

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.