A SURVEY ON TOWARD EFFECTIVE RESPONSE TO NATURAL DISASTERS: A DATA SCIENCE APPROACH

AUTHOR(S)

K.U.Ranjith, Dr. S. Karuppusamy

DOI: https://doi.org/10.46647/ijetms.2023.v07i02.072

ABSTRACT
Natural catastrophes have the potential to destroy large portions of infrastructure and kill thousands of people. Both the populace and the government find it challenging to deal with these situations. Particular attention must be given to the following two difficult problems: find a workable solution first evacuating people, then rebuilding homes and other infrastructure. Then, a successful recovery plan that prioritises the reconstruction of damaged areas and the evacuation of people can be a game-changer for overcoming those horrible circumstances. In this light, we introduce DiReCT, a method based on I a dynamic optimization model created to quickly develop an evacuation plan of an earthquake-stricken area, and ii) a double deep Q network-based decision support system capable of effectively guiding the rebuilding of the affected areas. The latter operates by taking into account the needs of the many stakeholders (such as citizens' social benefits and political priorities) as well as the resources available. The foundation for both of the aforementioned solutions is a specialized geographic data extraction Method called "GisToGraph," which was created expressly for this use. We used extensive GIS data, information on the vulnerability of urban land structures, and the historical city centre of L'Aquila (Italy) to test the applicability of the entire strategy.

Page No: 627 - 642

References:

[1] (Jul. 2020). (Jul. 2020). Social science analysis of objective and subjective data: implications for the smart citizen Retrieved on May 30, 2021. com/news/world-australia-53549936 [online].
[2] (Oct. 2020). ERuDite: The Educational Resource Discovery Index for Data Science, a service of the BD2K Training Coordinating Center. Retrieved on May 30, 2021.[Online]. Available: \shttps://www.bbc.com/news/world-europe-54749509 \s167842 Version 9, 2021Effective Response to Natural Disasters: A Data Science Approach, G. Mudassir et al.
[3] (Aug. 2020). (Aug. 2020). Contextual Markup and Mining for Science Learning in Digital Games: Linking Player Behaviors to Learning Objectives. Retrieved on May 30, 2021.[Online]. The following link is available: https://www.reuters.com/article/usafghanistan-floods-idUSKBN25M148
[4] (Nov. 2020). (Nov. 2020). CRISP-DM Twenty Years Later: Data Science Trajectories from Data Mining Processes. Retrieved on May 30, 2021.[Online].The following link is available: https://www.cbsnews.com/news/hurricane-eta-150-deadmissing-guatemala/
[5] (Nov. 2020). (Nov. 2020). 30 May 2021: Data Prospecting-A Step Towards Data Intensive Science [Online]. Available: \shttps://www.bbc.com/news/world-latin-america-54864963
[6] "Data Science Analysis and Profile Representation Applied to Secondary Prevention of Acute Coronary Syndrome," by R. Abdalla, is found at [6] SpringerPlus, 2016, pp. 1–10, vol. 5, no. 1.
[7] "Data Science as Political Action: Grounding Data Science in a Politics of Justice," Transp. Res. Rec., vol. 2198, no. 1, pp. 152-160, 2010. A. Abdelghany, K. Abdelghany, H. Mahmassani, H. Al-Ahmadi, and W. Alhalabi.
[8] A. Abdelghany, K. Abdelghany, H. Mahmassani, and W. Alhalabi, "Design and Evaluation of a Block-based Environment with a Data Science Context," Eur.
[9] "Distributed Data Strategies to Support Large-Scale Data Analysis Across Geo-Distributed Data Centers," Transp. Res. Rec. J. Transp. Res. Board, vol. 1939, no. 1, pp. 123–132, 2006. A. Abdelghany, K. Abdelghany, H. S. Mahmassani, and S. A. Al-Gadhi.
[10] "IEOS MLS Science Data Processing System: A Description of Architecture and Capabilities," in A View of Operations Research Applications in Italy, vol. 2, by C. Arbib, M. T. Moghaddam, and H. Muccini Springer, Cham, Switzerland, 2018, pp. 115–131.
[11] "Improving Urban Mobility by Defining a Smart Data Integration Platform," Math. Models Methods Appl. Sci., vol. 22, no. 2, August 2012, Art.no. 1230004; N. Bellomo, B. Piccoli, and A. Tosin.
[12] Intelligent Data Engineering for Migration to NoSQL Based Secure Environments, J. D. Brooks, K. Kar, and D. Mendonça, Proc. IEEE Int. Conf. Technol. Homeland Secur. (HST), Nov. 2013, pp. 504-510.
[13] "Leveraging Data Science to Combat COVID-19: A Comprehensive Review," in W. Choi, H. W. Hamacher, and S. Tufekci, "Eur. J. Operar. Res., vol. 35, no. 1, pp. 98-110, 1988.
[14] Parallel or Intersecting Lines? by D. Contreras, T. Blaschke, S. Kienberger, and P. Zeil. Int. J. Disaster Risk Reduction, vol. 8, pp. 125–142, June 2014. "Intelligent Bibliometrics for Investigating the Involvement of Data Science in Policy Analysis."
[15] "Passing the Data Baton: A Retrospective Analysis on Data Science Work and Workers," by M. Dolce and A. Goretti. 2015, August, Bull. Earthq. Eng., vol. 13, no. 8, pp. 2241-2264.
[16] "Proactive Scheduling and Resource Management for Connected Autonomous Vehicles: A Data Science Perspective," Transp. Res. C, Emerg. Technol., vol. 37, Dec. 2013, pp. 193-209. D. C. Duives, W. Daamen, and S. P. Hoogendoorn.
[17] Processes Meet Big Data: Connecting Data Science with Process Science, by M. S. Eid and I. H. El-Adaway, 17 J. Infrastructure Systems, September 2018, Vol. 24, No. 3, Art. No. 04018009.
[18] "SNP Data Science for Classification of Bipolar Disorder I and Bipolar Disorder," in Proc. 23rd iSTEAMS Conf., 2020, pp. 117–186. B. Eze and O. Olaiya.
[19] M. M. Fischer, "Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data," in Spatial Analysis and GeoComputation: Selected Essays, 2006, pages 43–60.
[20] "Toward Effective Response to Natural Disasters: A Data Science Approach," by P. Ghannad, Y.-C. Lee, C. J. Friedland, J. O. Choi, and E. Yang. 2020, July, J. Manage. Eng., vol. 36, no. 4, art.no. 04020038.
[21] ThirumoorthyPalanisamy, D. Alghazzawi, S. Bhatia, A. A. Malibari, P. Dadheeche and colleagues, "Improved energy-based multi-sensor object recognition in wireless sensor networks," Intelligent Automation & Soft Computing, vol. 33, no.1, pp. 227–244, 2022.
[22] P. "Improved key agreement based kerberos protocol for m-health security," Thirumoorthy, K. S. Bhuvaneshwari, C. Kamalanathan, P. Sunita, E. Prabhu et al., Computer Systems Science and Engineering, vol. 42, no.2, pp. 577–587, 2022.
[23] M.Deepika, S.Prabhu, M.Parvathi, and S.Hemalatha, "Cloud Task Scheduling Using Dynamic Algorithm", Gradiva Review Journal, Vol.8, No. 11, pages 53-60, 2022.
[24] S. "A research on routing strategy for in-network aggregation in wireless sensor networks," Sudha, B. Manimegalai, and P. Thirumoorthy, in Proc, IEEE ICCCI, Coimbatore, India, pp.1-4, 2014.
[25] P. N. Thirumoorthy and Thirumoorthy "Bayes node energy polynomial distribution to optimise routing in wireless sensor networks," K. Karthikeyan, PLoS ONE, vol. 10, no. 10: e0138932, pp.1-15, 2015.

How to Cite This Article:
K.U.Ranjith, Dr. S. Karuppusamy . A SURVEY ON TOWARD EFFECTIVE RESPONSE TO NATURAL DISASTERS: A DATA SCIENCE APPROACH . ijetms;7(2):627-642. DOI: 10.46647/ijetms.2023.v07i02.072