ABSTRACT
Disaster risk management has never been more important today; applying disaster risk reduction policies and strategies combined with current technologies today can diminish the effects of catastrophes and possibly increase the chances of preventing and reducing the damage of future disasters. With today's innovations in technology, surveying the impact of a disaster from multiple avenues is possible nowadays. Current day sensors can be remotely utilized to provide real-time data for accurate analysis and interpretation. Data sensed remotely can be used very efficiently and quickly to assess damage's severity and impact of floods for disaster risk management. Aerial surveillance of an afflicted area can provide next-level insight and depth. Visual imaging and 2D mapping benefit large-scale disaster-prone areas. Today, drone technology has greatly improved those various nations use it for multiple purposes, including disaster management. Mapping the terrain and analyzing the extent of the damage from the air is beneficial for post risk disaster management. This study developed a web-based system that utilizes data from sensors and drones used to map, measure, and ascertain the extent of damage to the flooded area. Testing made to the system shows that every function has passed its test case and is working accordingly. The User Acceptance Questionnaire administered gathered a satisfying response from the target beneficiaries of the system in the criteria of complexity, navigation, responsiveness, and ease of use. The interface design particularly the color pallet was also improved based on the mixed feedback from the users.
- Abad, R.P.B. and Fillone, A.M., 2019. Perceived risk of public transport travel during flooding events in Metro Manila, Philippines. Transportation research interdisciplinary perspectives, 2, p.100051.Google Scholar
- Reyes, P.J.D., Bornas, M.A.V., Dominey-Howes, D., Pidlaoan, A.C., Magill, C.R. and Solidum Jr, R.U., 2018. A synthesis and review of historical eruptions at Taal Volcano, Southern Luzon, Philippines. Earth-science reviews, 177, pp.565-588.Google Scholar
- Dasallas, L., An, H. and Lee, S., 2022. Developing an integrated multiscale rainfall-runoff and inundation model: Application to an extreme rainfall event in Marikina-Pasig River Basin, Philippines. Journal of Hydrology: Regional Studies, 39, p.100995.Google ScholarCross Ref
- Valenzuela, V.P.B., Esteban, M. and Onuki, M., 2020. Perception of Disasters and Land Reclamation in an Informal Settlement on Reclaimed Land: Case of the BASECO Compound, Manila, the Philippines. International Journal of Disaster Risk Science, 11(5), pp.640-654.Google ScholarCross Ref
- Kimuli, J.B., Di, B., Zhang, R., Wu, S., Li, J. and Yin, W., 2021. A multisource trend analysis of floods in Asia-Pacific 1990–2018: implications for climate change in sustainable development goals. International Journal of Disaster Risk Reduction, 59, p.102237.Google ScholarCross Ref
- Kedia, T., Ratcliff, J., O'Connor, M., Oluic, S., Rose, M., Freeman, J. and Rainwater-Lovett, K., 2020. Technologies enabling situational awareness during disaster response: a systematic review. Disaster Medicine and Public Health Preparedness, pp.1-19.Google Scholar
- Perera, D., Agnihotri, J., Seidou, O. and Djalante, R., 2020. Identifying societal challenges in flood early warning systems. International Journal of Disaster Risk Reduction, 51, p.101794.Google ScholarCross Ref
- Sahagun, M.A.M., Cruz, J.C.D. and Garcia, R.G., 2018. Nonlinear autoregressive with exogenous inputsneural network for water level prediction. In 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-6). IEEE.Google Scholar
- Noor, N.M., Abdullah, A. and Hashim, M., 2018, June. Remote sensing UAV/drones and its applications for urban areas: A review. In IOP conference series: Earth and environmental science (Vol. 169, No. 1, p. 012003). IOP Publishing.Google Scholar
- Wazid, M., Das, A.K., Kumar, N., Vasilakos, A.V. and Rodrigues, J.J., 2018. Design and analysis of secure lightweight remote user authentication and key agreement scheme in Internet of drones deployment. IEEE Internet of Things Journal, 6(2), pp.3572-3584.Google ScholarCross Ref
- Agudo, P.U., Pajas, J.A., Pérez-Cabello, F., Redón, J.V. and Lebrón, B.E., 2018. The potential of drones and sensors to enhance detection of archaeological cropmarks: A comparative study between multi-spectral and thermal imagery. Drones, 2(3), p.29.Google ScholarCross Ref
- Otto, A., Agatz, N., Campbell, J., Golden, B. and Pesch, E., 2018. Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey. Networks, 72(4), pp.411-458.Google ScholarCross Ref
- Noar, N.A.Z.M. and Kamal, M.M., 2017, November. The development of smart flood monitoring system using ultrasonic sensor with blynk applications. In 2017 IEEE 4th international conference on smart instrumentation, measurement and application (ICSIMA) (pp. 1-6). IEEE.Google Scholar
- Sheshu, E.D., Manjunath, N., Karthik, S. and Akash, U., 2018, August. Implementation of flood warning system using iot. In 2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT) (pp. 445-448). IEEE.Google Scholar
- Natividad, J.G. and Mendez, J.M., 2018, March. Flood monitoring and early warning system using ultrasonic sensor. In IOP conference series: materials science and engineering (Vol. 325, No. 1, p. 012020). IOP Publishing.Google Scholar
- Lara-Tuprio, D., Elvira, P., Bautista, E.P., Marcelo, R.M., Bataller, R.T., Esteban, D.A.B. and Yutuc, Y.P.B., 2018. Marikina flood hazard models using historical data of water level.Google Scholar
- Raspberry Pi, https://www.raspberrypi.org/Google Scholar
- Firebase, https://firebase.google.com/Google Scholar
- Geocoding API, https://docs.mapbox.com/api/search/geocoding/Google Scholar
- CKEditor5, https://ckeditor.com/ckeditor-5/Google Scholar
- WeatherWidget.io, https://weatherwidget.io/Google Scholar
- Lozañes, M.V.R., Nuñez, C.C., Zapanta, R.O., Soriano, A.J., Beaño, M.G.P., Magnate, M.B. and Medina, O.A., 2020, November. Web-based Riverbank Overflow Forecasting and Monitoring System. In 2020 IEEE REGION 10 CONFERENCE (TENCON) (pp. 602-607). IEEE.Google Scholar
- Bures, M., Cerny, T. and Ahmed, B.S., 2018, June. Internet of things: Current challenges in the quality assurance and testing methods. In International conference on information science and applications (pp. 625-634). Springer, Singapore.Google Scholar
Recommendations
Fuzzy risk analysis of flood disasters based on diffused-interior-outer-set model
Floods are indeed one of the most serious natural hazards for human societies, especially in China. In this paper, we firstly introduce the interior-outer-set model (IOSM) based on information diffusion theory in detail. Then taking consideration its ...
Rescue information system for earthquake disasters based on MANET emergency communication platform
IWCMC '09: Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World WirelesslyWhen stricken by a catastrophic natural disaster, emergency rescue operation is very critical to many lives. Many people trapped in the disastrous areas under collapsed buildings or landslides may have a large chance to survive if they are rescued in "...
Flood Detection and Warning System (FLoWS)
IMCOM '18: Proceedings of the 12th International Conference on Ubiquitous Information Management and CommunicationIn Malaysia, floods are the natural disasters that happen every year during the monsoon season from November until January. These flood caused serious damage to houses, roads, businesses, public facilities and even killed people. Though many steps have ...
Comments