EXPERIMENTAL STUDY OF IOT SENSOR PERFORMANCE FOR BUILDING MOVEMENT MONITORING

Authors

  • Sely Novita Sari
  • Bagus Gilang Pratama
  • Joko Prasojo

DOI:

https://doi.org/10.33579/krvtk.v10i2.6397

Keywords:

IoT, MEMS sensor, building movement, Structural Health Monitoring, smart infrastructure

Abstract

Real-time monitoring of building movement is essential to mitigate structural damage risks, particularly in earthquake-prone regions. The application of Internet of Things (IoT) technology enables continuous and efficient measurement of structural deformation and inclination through the integration of smart sensors and cloud-based systems. The primary objective of this study is to evaluate the performance of a MEMS-based IoT sensor system in detecting displacement and angular changes in building structures. An experimental laboratory test was conducted by comparing the readings of accelerometer, gyroscope, and inclinometer sensors with standard measuring instruments. Results indicate an average measurement error of 1.58%, a response time of 2.34 seconds, and data transmission reliability of 97.8%, demonstrating high accuracy and stability. The integration of sensors, an ESP32 microcontroller, and a cloud computing platform shows strong potential for implementation as an effective IoT-based Structural Health Monitoring (SHM) system, supporting the development of resilient and sustainable smart infrastructure

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References

A. Musyafa, “Procurement Planning of Livable Housing in Time Series for Balancing the Supply-Demand,” Jurnal Permukiman, vol. 18, no. 1, pp. 16–24, May 2023, doi: 10.31815/jp.2023.18.16-24.

A. Coates, M. Hammoudeh, and K. G. Holmes, “Internet of Things for Buildings Monitoring,” in Proceedings of the International Conference on Future Networks and Distributed Systems, New York, NY, USA: ACM, Jul. 2017. doi: 10.1145/3102304.3102342.

A. C. Martins, F. M. Costa Monobi, J. M. Roberto, P. H. Cerento de Lyra, and G. F. de Souza, “Development of an IoT-based Structural Parameter Monitoring System,” in 2023 Symposium on Internet of Things (SIoT), IEEE, Oct. 2023, pp. 1–5. doi: 10.1109/SIoT60039.2023.10390107.

P. Ragam and N. Devidas Sahebraoji, “Application of MEMS‐Based Accelerometer Wireless Sensor Systems for Monitoring of Blast‐Induced Ground Vibration and Structural Health: A Review,” IET Wireless Sensor Systems, vol. 9, no. 3, pp. 103–109, Jun. 2019, doi: 10.1049/iet-wss.2018.5099.

S. Balaji, S. Dhamodharan, and A. R. Aravind, “IOT Equipped Smart Building Monitoring and Control,” International Journal of Advance Research and Innovative Ideas in Education, vol. 5, no. 2, pp. 1230–1235, 2019, [Online]. Available: https://ijariie.com/AdminUploadPdf/IOT_Equipped_Smart_Building_Monitoring_and_Control_ijariie9809.pdf

J. Cao and X. Liu, Wireless Sensor Networks for Structural Health Monitoring. Springer International Publishing, 2016.

S. Traboulsi and S. Knauth, “Monitoring Tool for Improving Indoor Environment Quality and Performance Based on IoT Sensors: State of the Art and Concept,” in iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, Cham: Springer International Publishing, 2022, pp. 307–314. doi: 10.1007/978-3-030-92096-8_20.

H. F. Chang and T. K. Lin, “Real-Time Structural Health Monitoring System using Internet of Things and Cloud Computing,” in arXiv preprint arXiv:1901.00670, 2019.

H. Dang, M. Tatipamula, and H. X. Nguyen, “Cloud-Based Digital Twinning for Structural Health Monitoring Using Deep Learning,” IEEE Trans Industr Inform, vol. 18, no. 6, pp. 3820–3830, Jun. 2022, doi: 10.1109/TII.2021.3115119.

M. Flah, I. Nunez, W. B. Chaabene, and M. L. Nehdi, “Machine Learning Algorithms in Civil Structural Health Monitoring: A Systematic Review,” Archives of Computational Methods in Engineering, vol. 28, no. 4, pp. 2621–2643, Jun. 2021, doi: 10.1007/s11831-020-09471-9.

X. Hu, G. Olgun, and R. H. Assaad, “An Intelligent BIM-Enabled Digital Twin Framework for Real-Time Structural Health Monitoring using Wireless IoT Sensing, Digital Signal Processing, and Structural Analysis,” Expert Syst Appl, vol. 252, p. 124204, Oct. 2024, doi: 10.1016/j.eswa.2024.124204.

B. Santos, F. A. Silva, and A. Soares, “Redes de Sensores IoT em Edifícios Inteligentes: Uma Avaliação de Desempenho Usando Modelos de Filas,” in Anais do XX Workshop em Desempenho de Sistemas Computacionais e de Comunicação (WPerformance 2021), Sociedade Brasileira de Computação - SBC, Jul. 2021, pp. 25–36. doi: 10.5753/wperformance.2021.15720.

A. Bourechak, O. Zedadra, M. N. Kouahla, A. Guerrieri, H. Seridi, and G. Fortino, “At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives,” Sensors, vol. 23, no. 3, p. 1639, Feb. 2023, doi: 10.3390/s23031639.

F. Nyimbili and L. Nyimbili, “Types of Purposive Sampling Techniques with Their Examples and Application in Qualitative Research Studies,” British Journal of Multidisciplinary and Advanced Studies, vol. 5, no. 1, pp. 90–99, Feb. 2024, doi: 10.37745/bjmas.2022.0419.

E. Soltani, E. Ahmadi, F. Gueniat, and M. R. Salami, “A Review of Bridge Health Monitoring Based On Machine Learning,” Proceedings of the Institution of Civil Engineers - Bridge Engineering, vol. 178, no. 1, pp. 84–94, Feb. 2025, doi: 10.1680/jbren.22.00030.

L. U. Khan, I. Yaqoob, N. H. Tran, S. M. A. Kazmi, T. N. Dang, and C. S. Hong, “Edge-Computing-Enabled Smart Cities: A Comprehensive Survey,” IEEE Internet Things J, vol. 7, no. 10, pp. 10200–10232, Oct. 2020, doi: 10.1109/JIOT.2020.2987070.

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Published

2025-11-28

How to Cite

[1]
S. N. Sari, B. G. Pratama, and J. Prasojo, “EXPERIMENTAL STUDY OF IOT SENSOR PERFORMANCE FOR BUILDING MOVEMENT MONITORING”, Journal Technology of Civil, Electrical, Mechanical, Geology, Mining, and Urban Design, vol. 10, no. 2, Nov. 2025.