Correlation of Air, Surface and Pavement Temperatures using MPU 6050 Accelerometer Sensor

Authors

  • Teni Septiani Civil Engineering, Faculty of Engineering, Universitas Langlangbuana, Indonesia
  • Muhamad Rofi HM Civil Engineering, Faculty of Engineering, Universitas Langlangbuana, Indonesia
  • Siegfried Syafier Civil Engineering, Faculty of Engineering, Universitas Langlangbuana, Indonesia
  • Eko Wahyu Utomo Civil Engineering, Faculty of Engineering, Universitas Langlangbuana, Indonesia

DOI:

https://doi.org/10.24036/cived.v11i3.630

Keywords:

Accelerometer Sensor MPU 6050, Pearson Correlation Method, Temperature Correlation

Abstract

This research analyses the correlation between air temperature, road surface temperature and pavement temperature using the MPU 6050 accelerometer sensor and the Pearson correlation method. Temperature measurements were taken at several predetermined locations, with the data analysed to identify the correlation between the three types of temperature. The analysis showed a very strong correlation between air temperature and road surface temperature, with a correlation coefficient of 0.7845 at night and 0.9663 during the day. Similarly, there is a very strong correlation between road surface temperature and pavement temperature, with a correlation coefficient of 0.8482 at night and 0.9673 during the day. These findings indicate that an increase in road surface temperature leads to an increase in pavement temperature. It was concluded that the correlation method can be used to predict temperatures at other points without invasive direct measurements, thus preventing damage to the road due to destructive measurements. This method is recommended as an alternative in pavement temperature monitoring.

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Published

2024-09-30

How to Cite

Septiani, T., HM, M. R., Syafier, S., & Utomo, E. W. (2024). Correlation of Air, Surface and Pavement Temperatures using MPU 6050 Accelerometer Sensor. CIVED, 11(3), 964–974. https://doi.org/10.24036/cived.v11i3.630

Issue

Vol. 11 No. 3 (2024): September 2024

Section

Articles

License

Copyright (c) 2024 Teni Septiani, Muhamad Rofi HM, Siegfried Syafier, Eko Wahyu Utomo

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.