Journal of Information Systems Engineering and Management

Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry
Chao Kong 1, Arthit Petchsasithon 2 *
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1 Master student, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand
2 Assistant Professor, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 1, Article No: 25183
https://doi.org/10.55267/iadt.07.14315

Published Online: 26 Jan 2024

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How to cite this article
APA 6th edition
In-text citation: (Kong & Petchsasithon, 2024)
Reference: Kong, C., & Petchsasithon, A. (2024). Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry. Journal of Information Systems Engineering and Management, 9(1), 25183. https://doi.org/10.55267/iadt.07.14315
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Kong C, Petchsasithon A. Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry. J INFORM SYSTEMS ENG. 2024;9(1):25183. https://doi.org/10.55267/iadt.07.14315
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Kong C, Petchsasithon A. Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry. J INFORM SYSTEMS ENG. 2024;9(1), 25183. https://doi.org/10.55267/iadt.07.14315
Chicago
In-text citation: (Kong and Petchsasithon, 2024)
Reference: Kong, Chao, and Arthit Petchsasithon. "Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry". Journal of Information Systems Engineering and Management 2024 9 no. 1 (2024): 25183. https://doi.org/10.55267/iadt.07.14315
Harvard
In-text citation: (Kong and Petchsasithon, 2024)
Reference: Kong, C., and Petchsasithon, A. (2024). Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry. Journal of Information Systems Engineering and Management, 9(1), 25183. https://doi.org/10.55267/iadt.07.14315
MLA
In-text citation: (Kong and Petchsasithon, 2024)
Reference: Kong, Chao et al. "Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry". Journal of Information Systems Engineering and Management, vol. 9, no. 1, 2024, 25183. https://doi.org/10.55267/iadt.07.14315
ABSTRACT
Using a novel methodology that integrates incremental dynamic analysis (IDA) and unmanned aerial vehicle positioning (POS) analysis, this study aims to assess the seismic risk of brick structures in rural China. This method can collect a lot of data and accurately anticipate seismic damage by combining UAV oblique photography with IDA analysis. Because rural China has many masonry structures, the project will design unique seismic risk mitigation strategies. High-resolution cameras on Unmanned Aerial Vehicles capture realistic photographs of rural brick buildings. The collected data is carefully examined to reveal architectural and structural elements. The project uses dynamic post-processing software from the CHC Geomatics Office to improve UAV-reference station position accuracy. This program analyzes UAV POS data disparities. The findings allow rural Chinese brick buildings to be assessed for seismic sensitivity during unexpected ground shaking occurrences. UAV tilt-photography reduces manpower and expenditures, improving inquiry efficiency. This combination improves seismic risk response. The IDA and UAV POS analysis are essential for earthquake preparedness and risk mitigation. This data-driven method informs lawmakers, urban planners, and disaster management authorities worldwide, improving earthquake engineering and catastrophe resilience programs. This work improves seismic threat assessment and masonry structure fortification, making earthquake-prone buildings safer. Thus, rural communities benefit from it.
KEYWORDS
REFERENCES
  • Adhikari, R. K., & D’Ayala, D. (2020). 2015 Nepal earthquake: Seismic performance and post-earthquake reconstruction of stone in mud mortar masonry buildings. Bulletin of earthquake engineering, 18, 3863-3896.
  • Ansari, A., Rao, K. S., & Jain, A. K. (2023). Application of microzonation towards system-wide seismic risk assessment of railway network. Transportation Infrastructure Geotechnology, 1-24.
  • Aydogdu, H. H., Demir, C., Comert, M., Kahraman, T., & Ilki, A. (2023). Structural characteristics of the earthquake-prone building stock in Istanbul and prioritization of existing buildings in terms of seismic risk—A pilot project conducted in Istanbul. Journal of earthquake engineering, 1-25.
  • Burdziakowski, P. (2020). A novel method for the deblurring of photogrammetric images using conditional generative adversarial networks. Remote Sensing, 12(16), 2586.
  • Cattari, S., Angiolilli, M., Alfano, S., Brunelli, A., & De Silva, F. (2022, 2022). Investigating the combined role of the structural vulnerability and site effects on the seismic response of a URM school hit by the Central Italy 2016 earthquake. In Structures (pp. 386-402). Amsterdam, Netherlands: Elsevier.
  • Chaudhary, M. T., & Piracha, A. (2021). Natural disasters—Origins, impacts, management. Encyclopedia, 1(4), 1101-1131.
  • Chen, K., Reichard, G., Xu, X., & Akanmu, A. (2023). GIS-based information system for automated building façade assessment based on unmanned aerial vehicles and artificial intelligence. Journal of Architectural Engineering, 29(4). https://doi.org/10.1061/JAEIED.AEENG-1635
  • Cui, P., Ge, Y., Li, S., Li, Z., Xu, X., Zhou, G. G. D., ... Zhou, L. (2022). Scientific challenges in disaster risk reduction for the Sichuan–Tibet railway. Engineering Geology, 309, 106837.
  • Dindaroğlu, T., Kılıç, M., Günal, E., Gündoğan, R., Akay, A. E., & Seleiman, M. (2022). Multispectral UAV and satellite images for digital soil modeling with gradient descent boosting and artificial neural network. Earth Science Informatics, 15(4), 2239-2263.
  • Elliott, J. R. (2020). Earth observation for the assessment of earthquake hazard, risk and disaster management. Surveys in Geophysics, 41(6), 1323-1354.
  • Euchi, J. (2021). Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems?. Chinese Journal of Aeronautics, 34(2), 182-190.
  • Feroz, S., & Abu Dabous, S. (2021). Uav-based remote sensing applications for bridge condition assessment. Remote Sensing, 13(9), 1809.
  • Freddi, F., Galasso, C., Cremen, G., Dall’Asta, A., Di Sarno, L., Giaralis, A., ... Petrone, C. (2021). Innovations in earthquake risk reduction for resilience: Recent advances and challenges. International Journal of Disaster Risk Reduction, 60, 102267.
  • Furtado, A. F. C. A. (2020). Seismic vulnerability assessment and retrofitting strategies for masonry infilled frame buildings considering in-plane and out-of-plane behaviour. (Doctoral dissertation, Universidade do Porto, Porto, Portugal). Retrieved from https://fe.up.pt/construct/scientific-outcomes/seismic-vulnerability-assessment-and-retrofitting-strategies-for-masonry-infilled-frame-buildings-considering-in-plane-and-out-of-plane-behaviour/
  • Giordan, D., Adams, M. S., Aicardi, I., Alicandro, M., Allasia, P., Baldo, M., ... Hobbs, P. (2020). The use of unmanned aerial vehicles (UAVs) for engineering geology applications. Bulletin of Engineering Geology and the Environment, 79, 3437-3481.
  • Godínez-Domínguez, E. A., Tena-Colunga, A., Pérez-Rocha, L. E., Archundia-Aranda, H. I., Gómez-Bernal, A., Ruiz-Torres, R. P., & Escamilla-Cruz, J. L. (2021). The September 7, 2017 Tehuantepec, Mexico, earthquake: Damage assessment in masonry structures for housing. International Journal of Disaster Risk Reduction, 56, 102123.
  • Greco, R., Barca, E., Raumonen, P., Persia, M., & Tartarino, P. (2023). Methodology for measuring dendrometric parameters in a Mediterranean forest with UAVs flying inside forest. International Journal of Applied Earth Observation and Geoinformation, 122, 103426.
  • Guzmán, S. A., Fóster, P. F., Ramírez-Correa, P., Grandón, E. E., & Alfaro-Perez, J. (2018). Information systems and their effect on organizational performance: An inquiry into job satisfaction and commitment in higher education institutions. Journal of Information Systems Engineering and Management, 3(4), 26.
  • Hobbs, T. E., Journeay, J. M., Rao, A. S., Kolaj, M., Martins, L., LeSueur, P., ... Johnson, K. (2023). A national seismic risk model for Canada: Methodology and scientific basis. Earthquake Spectra, 87552930231173446.
  • Hussain, Y., Schlögel, R., Innocenti, A., Hamza, O., Iannucci, R., Martino, S., & Havenith, H. B. (2022). Review on the geophysical and UAV-based methods applied to landslides. Remote Sensing, 14(18), 4564.
  • Işık, E., Hadzima-Nyarko, M., Bilgin, H., Ademović, N., Büyüksaraç, A., Harirchian, E., ... Aghakouchaki Hosseini, S. E. (2022). A comparative study of the effects of earthquakes in different countries on target displacement in mid-rise regular RC structures. Applied Sciences, 12(23), 12495.
  • Jena, R., & Pradhan, B. (2020). Integrated ANN-cross-validation and AHP-TOPSIS model to improve earthquake risk assessment. International Journal of Disaster Risk Reduction, 50, 101723.
  • Kumar, A., Krishnamurthi, R., Sharma, G., Jain, S., Srikanth, P., Sharma, K., & Aneja, N. (2023). Revolutionizing modern networks: Advances in AI, machine learning, and blockchain for quantum satellites and UAV-based communication. arXiv preprint arXiv:2303.11753.
  • Levine, N. M., & Spencer Jr, B. F. (2022). Post-earthquake building evaluation using UAVs: A BIM-based digital twin framework. Sensors, 22(3), 873.
  • Li, G., Zhang, P., Dong, Z., & Yu, L. (2022). Intelligent information acquisition methods and seismic damage prediction of rural masonry building groups. Journal of Building Structures, 43(8), 196.
  • Li, T., & Hu, H. (2021). Development of the use of Unmanned Aerial Vehicles (UAVs) in emergency rescue in China. Risk Management and Healthcare Policy, 4293-4299.
  • Menna, C., Felicioni, L., Negro, P., Lupíšek, A., Romano, E., Prota, A., & Hájek, P. (2022). Review of methods for the combined assessment of seismic resilience and energy efficiency towards sustainable retrofitting of existing European buildings. Sustainable Cities and Society, 77, 103556.
  • Mishra, P., & Singh, G. (2023). Unmanned aerial vehicles in sustainable smart cities. In Sustainable smart cities: Enabling technologies, energy trends and potential applications (pp. 221-238). Cham, Switzerland: Springer.
  • Nikolić, Ž., Runjić, L., Ostojić Škomrlj, N., & Benvenuti, E. (2021). Seismic vulnerability assessment of historical masonry buildings in Croatian coastal area. Applied Sciences, 11(13), 5997.
  • Oliveira, C. S. (2022). The main developments of seismology and earthquake engineering since the early 1700s and the new challenges for a sustainable society. Bulletin of earthquake engineering, 20(10), 4697-4863.
  • Parra, D. T., & Guerrero, C. D. (2020). Technological variables for decision-making IoT adoption in small and medium enterprises. Journal of Information Systems Engineering and Management, 5(4), em0124.
  • Rachmawati, T. S. N., & Kim, S. (2022). Unmanned Aerial Vehicles (UAV) integration with digital technologies toward construction 4.0: A systematic literature review. Sustainability, 14(9), 5708.
  • Rejeb, A., Rejeb, K., Simske, S., & Treiblmaier, H. (2021). Humanitarian drones: A review and research agenda. Internet of Things, 16, 100434.
  • Shareef, S. S. (2023). Earthquake consideration in architectural design: Guidelines for architects. Sustainability, 15(18), 13760.
  • Sharma, V. B., Tewari, S., Biswas, S., Lohani, B., Dwivedi, U. D., Dwivedi, D., ... Jung, J. P. (2021). Recent advancements in AI-enabled smart electronics packaging for structural health monitoring. Metals, 11(10), 1537.
  • Soleymani, A., Jahangir, H., & Nehdi, M. L. (2023). Damage detection and monitoring in heritage masonry structures: Systematic review. Construction and Building Materials, 397, 132402.
  • Stepinac, M., Lourenço, P. B., Atalić, J., Kišiček, T., Uroš, M., Baniček, M., & Novak, M. Š. (2021). Damage classification of residential buildings in historical downtown after the ML5. 5 earthquake in Zagreb, Croatia in 2020. International Journal of Disaster Risk Reduction, 56, 102140.
  • Utkucu, M., Kurnaz, T. F., & İnce, Y. (2023). The seismicity assessment and probabilistic seismic hazard analysis of the plateau containing large dams around the East Anatolian Fault Zone, Eastern Türkiye. Environmental Earth Sciences, 82(15), 371.
  • Wang, C., Si, G., Zhang, C., Cao, A., & Canbulat, I. (2021). Location error based seismic cluster analysis and its application to burst damage assessment in underground coal mines. International Journal of Rock Mechanics and Mining Sciences, 143, 104784.
  • Wang, J., & Ueda, T. (2023a, June). Application of Unmanned Aerial Vehicle (UAV) technology on damage inspection of reinforced concrete structures. In International Symposium of the International Federation for Structural Concrete (pp. 1461-1470). Cham, Switzerland: Springer.
  • Wang, J., & Ueda, T. (2023b). A review study on unmanned aerial vehicle and mobile robot technologies on damage inspection of reinforced concrete structures. Structural Concrete, 24(1), 536-562.
  • Wang, S., Rodgers, C., Zhai, G., Matiki, T. N., Welsh, B., Najafi, A., ... Spencer Jr, B. F. (2022). A graphics-based digital twin framework for computer vision-based post-earthquake structural inspection and evaluation using unmanned aerial vehicles. Journal of Infrastructure Intelligence and Resilience, 1(1), 100003.
  • Wankmüller, C., Kunovjanek, M., & Mayrgündter, S. (2021). Drones in emergency response—Evidence from cross-border, multi-disciplinary usability tests. International Journal of Disaster Risk Reduction, 65, 102567.
  • Yao, H., Qin, R., & Chen, X. (2019). Unmanned aerial vehicle for remote sensing applications—A review. Remote Sensing, 11(12), 1443.
  • Zhang, Y., Fung, J. F., Johnson, K. J., & Sattar, S. (2022). Review of seismic risk mitigation policies in earthquake-prone countries: lessons for earthquake resilience in the United States. Journal of earthquake engineering, 26(12), 6208-6235.
  • Zhang, Y., Guo, H., Yin, W., Zhao, Z., & Lu, C. (2023). Earthquake-induced building damage recognition from unmanned aerial vehicle remote sensing using scale-invariant feature transform characteristics and support vector machine classification. Earthquake Spectra, 39(2), 962-984.
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