Smart Structures and Systems

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Smart monitoring system with multi-criteria decision using a feature based computer vision technique

  • Lin, Chih-Wei (Department of Computer Science and Information Engineering, National Taiwan University) ;
  • Hsu, Wen-Ko (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chiou, Dung-Jiang (Research Center for Hazard Mitigation and Prevention, National Central University) ;
  • Chen, Cheng-Wu (Department of Maritime Information and Technology, National Kaohsiung Marine University) ;
  • Chiang, Wei-Ling (Department of Civil Engineering, National Central University)
  • Received : 2014.03.18
  • Accepted : 2014.07.07
  • Published : 2015.06.25
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Abstract

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.

Keywords

References

  1. Alcantara-Ayala, I. (2002), "Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries", Geomorphology, 47(2), 107-124. https://doi.org/10.1016/S0169-555X(02)00083-1
  2. Allen, R.M. and Kanamori, H. (2003), "The potential for earthquake early warning in southern California", Science, 300(5620), 786-789. https://doi.org/10.1126/science.1080912
  3. Arattano, M. and Marchi, L. (2008), "Systems and sensors for debris-flow monitoring and warning", Sensors, 8(4), 2436-2452. https://doi.org/10.3390/s8042436
  4. Bay, H., Tuytelaars, T. and Van Gool, L. (2006), "Surf: Speeded up robust features", Proceeding of the 9th European Conference on Computer Vision (ECCV'06), Graz, Austria, May.
  5. Cho, C.Y., Chou, P.H., Chung, Y.C., King, C.T., Tsai, M.J., Lee, B.J., and Chou, T.Y. (2008), "Wireless sensor networks for debris flow observation", Proceeding of the 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, San Francisco, CA, June.
  6. Douglas, J. (2007), "Physical vulnerability modelling in natural hazard risk assessment", Natural Hazards and Earth System Science, 7(2), 283-288. https://doi.org/10.5194/nhess-7-283-2007
  7. Department of Civil Engineering National Taiwan University, http://www.ntuce-newsletter.tw/vol.45/T4_1.html, Accessed 2013.
  8. Ellingwood, B.R. (2001), "Earthquake risk assessment of building structures", Reliab. Eng. Syst. Safe, 74(3), 251-262. https://doi.org/10.1016/S0951-8320(01)00105-3
  9. Erdik, M., Aydinoglu, N., Fahjan, Y., Sesetyan, K., Demircioglu, M., Siyahi, B., Durukal, E., Ozbey, C., Biro, Y. and Akman, H..(2003), "Earthquake risk assessment for Istanbul metropolitan area", Earthq. Eng. Eng. Vib., 2(1), 1-23. https://doi.org/10.1007/BF02857534
  10. Faber, M. and Stewart, M. (2003), "Risk assessment for civil engineering facilities: critical overview and discussion", Reliab. Eng. Syst. Safe, 80(2), 173-184. https://doi.org/10.1016/S0951-8320(03)00027-9
  11. Greidanus, H., Dekker, R., Caliz, J. and Rodrigues, A. (2005), "Tsunami damage assessment with satellite radar", Proceeding of the URSI 2005 Commission F Symposium on Microwave Remote Sensing of the Earth, Oceans, Ice, and Atmosphere, Ispra, Italy.
  12. He, X.W., Mitsuo, K., Hayashikawa, T., Kim, C.W., Necati Catbas, F. and Furuta, H. (2014), "A structural damage detection approach using train-bridge interaction analysis and soft computing methods", Smart Struct. Syst., 13(5), 869-890. https://doi.org/10.12989/sss.2014.13.5.869
  13. Hsu, W.K., Huang, P.C., Chang, C.C., Chen, C.W., Hung, D.M. and Chiang, W.L. (2011), "An integrated flood risk assessment model for property insurance industry in Taiwan", Natural hazards, 58(3), 1295-1309. https://doi.org/10.1007/s11069-011-9732-9
  14. Hsu, W.K., Tseng, C.P., Chiang, W.L. and Chen, C.W. (2012), "Risk and uncertainty analysis in the planning stages of a risk decision-making process", Natural Hazards, 61(3), 1355-1365. https://doi.org/10.1007/s11069-011-0032-1
  15. Heaton, T. H. (1985), "A model for a seismic computerized alert network", Science, 228(4702), 987-990. https://doi.org/10.1126/science.228.4702.987
  16. Jaffe, B.E. and Gelfenbaum, G. (2002), "Using tsunami deposits to improve assessment of tsunami risk", Solutions to Coastal Disasters, 2, 836-847.
  17. Jin, Y.Q. and Xu, F. (2011), "Monitoring and early warning the debris flow and landslides using VHF radar pulse echoes from layering land media", Geosci. Remote Sens. Letters, 8(3), 575-579. https://doi.org/10.1109/LGRS.2010.2093598
  18. Kanamori, H. (2005), "Real-time seismology and earthquake damage mitigation", Annu. Rev. Earth Pl. Sc., 33, 195-214. https://doi.org/10.1146/annurev.earth.33.092203.122626
  19. Kanamori, H., Hauksson, E. and Heaton, T. (1997), "Real-time seismology and earthquake hazard mitigation", Nature, 390, 461-464. https://doi.org/10.1038/37280
  20. Khajehzadeh, M., Taha, M.R. and Eslami, M. (2014), "Multi-objective optimization of foundation using global-local gravitational search algorithm", Struct. Eng. Mech., 50(3), 257-273. https://doi.org/10.12989/sem.2014.50.3.257
  21. Lili, T., Deyong, H., Xiaojuan, L. and Jian, L. (2010), "Change detection of landslides and debris in south Taiwan after Morakot typhoon based on HJ-1-B Satellite images", Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Honolulu, HI, July.
  22. Lee, H.C., Banerjee, A., Fang, Y.M., Lee, B.J. and King, C.T. (2010), "Design of a multifunctional wireless sensor for in-situ monitoring of debris flows", Instrumentation and Measurement, IEEE Transactions on, 59(11), 2958-2967. https://doi.org/10.1109/TIM.2010.2046361
  23. Lee, H.C., Cho, C.Y., King, C.T., Fang, Y.M. and Lee, B.J. (2009), "Design and implementation of non-autonomous mobile wireless sensor for debris flow monitoring", Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems(MASS'09), Macau, October.
  24. Lin, C.W., Hung, Y.P., Hsu, W.K., Chiang, W.L. and Chen, C.W. (2013a), "The construction of a high-resolution visual monitoring for hazard analysis", Natural Hazards, 65(3), 1285-1292. https://doi.org/10.1007/s11069-012-0409-9
  25. Lin, C.W., Chen, C.W., Hsu, W.K., Chen, C.Y., Tsai, C.H., Hung, Y.P. and Chiang, W.L. (2013b), "Application of a feature-based approach to debris flow detection by numerical simulation", Natural Hazards, 67(2), 1-14. https://doi.org/10.1007/s11069-011-9901-x
  26. Lugeri, N., Kundzewicz, Z., Genovese, E., Hochrainer, S. and Radziejewski, M. (2010), "River flood risk and adaptation in Europe-assessment of the present status", Mitigation and Adaptation Strategies for Global Change, 15(7), 621-639. https://doi.org/10.1007/s11027-009-9211-8
  27. Markus, A.A., Courage, W.M.G. and van Mierlo, M.C.L.M. (2010), "A computational framework for flood risk assessment in The Netherlands", Scientific Programming, 18(2), 93-105. https://doi.org/10.1155/2010/782402
  28. Nakamura, Y. (1988), "On the urgent earthquake detection and alarm system (UrEDAS)", Proceeding of the 9th World Conference on Earthquake Engineering, Tokyo-Kyoto, Japan, August.
  29. National Applied Research Laboratories, http://3dgis.colife.org.tw/technology_multi_scale_application.aspx, Accessed 2013, 2013.
  30. Okal, E.A., Piatanesi, A. and Heinrich, P. (1999), "Tsunami detection by satellite altimetry", J. Geophys. Res., 104(1), 599-615. https://doi.org/10.1029/1998JB000018
  31. Pandey, A.C., Singh, S. and Nathawat, M.S. (2010), "Waterlogging and flood hazards vulnerability and risk assessment in Indo Gangetic plain", Natural Hazards, 55(2), 273-289. https://doi.org/10.1007/s11069-010-9525-6
  32. Rau, J.Y., Chen, L.C., Liu, J.K. and Wu, T.H. (2007), "Dynamics monitoring and disaster assessment for watershed management using time-series satellite images", IEEE T. Geosci. Remote, 45(6), 1641. https://doi.org/10.1109/TGRS.2007.894928
  33. Soil and Water Conservation Bureau and F. C. U. GIS research center, http://246.swcb.gov.tw/default-1.asp, Accessed 2013, 2013.
  34. Stramondo, S., Bignami, C., Chini, M., Pierdicca, N. and Tertulliani, A. (2006), "Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies", Int. J. Remote Sens., 27(20), 4433-4447. https://doi.org/10.1080/01431160600675895
  35. Van Aalst, M.K. (2006), "The impacts of climate change on the risk of natural disasters", Disasters, 30(1), 5-18. https://doi.org/10.1111/j.1467-9523.2006.00303.x
  36. Wu, Y.M., Lee, W.H., Chen, C.C., Shin, T.C., Teng, T.L. and Tsai, Y.B. (2000), "Performance of the Taiwan rapid earthquake information release system (RTD) during the 1999 Chi-Chi (Taiwan) earthquake", Seismol. Res. Lett., 71(3), 338-343. https://doi.org/10.1785/gssrl.71.3.338
  37. Wu, Y.M., Shin, T.C. and Tsai, Y.B. (1998), "Quick and reliable determination of magnitude for seismic early warning", Bulletin of the Seismological Society of America, 88(5), 1254-1259.
  38. Wu, Y.M. and Teng, T. (2002), "A virtual subnetwork approach to earthquake early warning", Bulletin of the Seismological Society of America, 92(5), 2008-2018. https://doi.org/10.1785/0120010217
  39. Wu, Y.M. and Zhao, L. (2006), "Magnitude estimation using the first three seconds P-wave amplitude in earthquake early warning", Geophys. Res. Lett., 33(16), L16312. https://doi.org/10.1029/2006GL026871

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