Optimizing Disaster Management with Blockchain Technology: A Decision Support System for Disaster Risk Reduction and Management
Keywords:
Blockchain, blockchain technology, cordillera , decision support system, disaster, disaster management, disaster risk reduction and management, tropical cyclonesAbstract
As technology advances, the enhancement and development of disaster-related remains limited, and disaster management at the regional level is prompt to actively collect and deliver information at a fast pace while deriving comprehensive disaster insights in real time. However, many organizations still rely on manual reporting as it requires formatting, sorting and proofreading that leads to time consuming, data duplication and delays in decision-making and inefficiencies due to lack of appropriate tools to enhance the organization’s productivity. To address these challenges, the researcher developed a Decision Support System with blockchain technology for Disaster Risk Reduction Management for the Office of the Civil Defense Cordillera Administrative Region. This system standardized disaster risk management system and enables for regional agencies to deliver efficiently in near real-time scenario. Additionally, it facilitates streamlined analysis and secure data storage, allowing duty officers to visualize the current situation more effectively. Future researchers can further enhance the system’s functionality by adding recommended features such as AI monitoring and notification, import and export of situational reports from different line agencies, plotting of tropical cyclones related incidents, earthquake and fire incident monitoring.
Downloads
References
Natural Disasters Data Book-2011 (2012). analyzed by Asian Disaster Reduction Center by CRED EM-DAT database, Retrieved November 12, 2023.
International Red Cross (2020), What is a disaster? Retrieved June 26, 2024.
Philippine Institute for Development Studies. (2020). Estimating the economic costs of natural disasters in the Philippines. Retrieved from PIDS website July 14, 2024.
Alcayna, T., Bollettino, V., Dy, P., & Vinck, P. (2020). Resilience and disaster risk reduction: A Philippines case study. Journal of Disaster Risk Management, 5(1), 34-45.
Bettencourt, L. M., Cintra, R. J., & De la Rosa, D. (2021). The role of satellite technology in disaster management: A focus on tropical cyclones. Journal of Remote Sensing and GIS, 12(4), 567-580.
Castañeda, R. D., & Perez, M. G. (2019). Flood Monitoring and Early Warning Systems in the Philippines: Implementation and impact. Journal of Environmental Monitoring and Assessment, 54(2), 123-135.
Chaiir, S., Charrad, M., & Bellamine Ben Saoud, N. (2023). Automatic identification of assistance needs in disaster situations using hybrid word embedding techniques. In Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation (pp. 510-515). Association for Computational Linguistics.
Cova, T. J., Dennison, P. E., & Drews, F. A. (2019). GIS and remote sensing technologies in disaster risk management. Journal of Disaster Research, 14(1), 88-102.
Cruz, R. V., & David, M. P. (2020). The impact of tropical cyclones on agricultural productivity in the Cordillera region, Philippines. Philippine Journal of Agricultural Economics, 77(3), 201-214.
World Meteorological Organization (2019). Tropical Cyclone. Retrieved June 26, 2024.
Cutter, S. L. (2020). Global vulnerabilities to natural disasters: A growing concern in the face of climate change. Global Environmental Change,63, 102-117.https://doi.org/10.1016/j.gloenvcha.2020.102017
Delos Reyes, R. A., Serrano, M. J., & Villar, C. F. (2020). Community-based disaster risk reduction: Lessons from Benguet province. Philippine Journal of Public Administration, 64(1), 34-50.
Cao, F.F., Xu, X.F., Zhang, C.L., Kong, W.B., 2023. Evaluation of urban flood resilience and its Space-Time Evolution: a case study of Zhejiang Province. China. Ecol. Indic.154, 110643.
Thanvisitthpon, N., Shrestha, S., Pal, I., Ninsawat, S., Chaowiwat, W., 2020. Assessment of flood adaptive capacity of urban areas in Thailand. Environ. Impact Assess. Rev.81, 106363.
Liu, F., Xu, E., Zhang, H., 2022. An improved typhoon risk model coupled with mitigation capacity and its relationship to disaster losses. J. Clean. Prod. 357,131913.
Wang, T., Wu, S., Gao, J., Wei, B., 2022. Coping Capacity Assessment of Regional Typhoon-flood-geological Disaster Chain. J. Catastrophol. 37 (193–200), 210.
Rafliana, I., et al., 2022. Tsunami risk communication and management: contemporary gaps and challenges. Int. J. Disaster Risk Reduction 70, 102771.
Shuai, X., Lei, Z., Jun, X., Yi, D., Yang, Z., Yao, T., 2023. Assessment of the urban waterlogging resilience and identification of its driving factors: a case study of Wuhan City. China. Sci. Total Environ. 866, 161321.
Harvard Business School Online (2022), What Is Design Thinking & Why Is It Important?, Retrieved August 1, 2024.
Shojaei, D., Kalantari, M., Bishop, I. D., Rajabifard, A., & Aien, A. (2013). Visualization requirements for 3D cadastral systems. Computers, Environment and Urban Systems, 41, 39–54. doi:10.1016/j.compenvurbsys.2013.
T. Knutson, S.J. Camargo, J.C.L. Chan, K. Emanuel, C.-H. Ho, J. Kossin, M. Mohapatra, M. Satoh, M. Sugi, K. Walsh, L. Wu (2020). Tropical cyclones and climate change assessment: Part II: projected response to anthropogenic warming. Bull. Am. Meteorol. Soc., 101 (2020), pp. E303-E322, 10.1175/BAMS-D-18-0194.1.
S. Hallegatte, A. Vogt-Schilb, J. Rozenberg, M. Bangalore, C. Beaudet. (2020). From poverty to disaster and back: a review of literature. Econ. Disasters Clim. Change, 4 (2020), pp. 223-247.
SRMTech (2023). Everything about Feature Driven Development (FDD). Retrieved from srmtech website August 2, 2024.
Laura Fitzgibbons (2024). feature-driven development (FDD). Retrieved from techtarget website August August 2, 2024.
LaunchDarkly (2021). Feature-Driven Development: A Brief Overview. Retrieved from launchDarkly website August 2, 2024.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
