Harnessing Mobile Technology for Flood Disaster Readiness and Response: A Comprehensive Review of Mobile Applications on the Google Play Store

Urban Science, Год журнала: 2025, Номер 9(4), С. 106 - 106

Опубликована: Апрель 1, 2025

The increasing frequency and severity of disasters in urban areas demand sustainable, smart disaster management strategies to leverage technological advancements. This study provides a comprehensive review mobile apps for awareness available the Google Play Store, with particular emphasis on addressing flood readiness response. Mobile have become indispensable tools disseminating immediate notifications, facilitating emergency communication, coordinating response activities. A total 77 Store were identified evaluated using systematic search. evaluation criteria included user ratings, download counts, key crisis functionalities such as real-time alerts, contact directories, preparedness checklists, reporting capabilities. findings emphasised following: (a) importance integrating cutting-edge technologies, i.e., AI IoT, enhance functionality, accuracy, capacity applications; (b) use crowdsourcing valuable mechanism enriching inclusive responsible data; (c) enabling timely updates fostering community engagement; (d) establishing agency engagements, gamified elements, reciprocal communication tools, push-to-talk features ensure long-term sustainability apps. By incorporating these insights, can significantly resilience improve effectiveness responding natural this digital age.

Язык: Английский

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A decision-making tool for the determination of the distribution center location in a humanitarian logistics network

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122010 - 122010

Опубликована: Окт. 9, 2023

Язык: Английский

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Efficient offloading in disaster-affected areas using unmanned aerial vehicle-assisted mobile edge computing: A gravitational search algorithm-based approach

International Journal of Disaster Risk Reduction, Год журнала: 2023, Номер 97, С. 104067 - 104067

Опубликована: Окт. 1, 2023

Язык: Английский

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Strategies for Humanitarian Logistics and Supply Chain in Organizational Contexts: Pre- and Post-Disaster Management Perspectives

Systems, Год журнала: 2024, Номер 12(6), С. 215 - 215

Опубликована: Июнь 18, 2024

Every organization typically comprises various internal components, including regional branches, operations centers/field offices, major transportation hubs, and operational units, among others, housing a population susceptible to disaster impacts. Moreover, organizations often possess resources such as staff, vehicles, medical facilities, which can mitigate human casualties address needs across affected areas. However, despite the importance of managing disasters within organizational networks, there remains research gap in development mathematical models for scenarios, specifically incorporating offices external stakeholders relief centers. Addressing this gap, study examines an optimization model both before after planning humanitarian supply chain logistical framework organization. The areas are defined stakeholders, facilities. A mixed-integer nonlinear is formulated minimize overall costs, considering factors penalty costs untreated injuries demand, delays rescue item distribution operations, waiting injured emergency vehicles air ambulances. implemented using GAMS software 47.1.0 test problems different scales, with Grasshopper Optimization Algorithm proposed larger-scale scenarios. Numerical examples provided show effectiveness feasibility validate metaheuristic approach. Sensitivity analysis conducted assess model’s performance under conditions, key managerial insights implications discussed.

Язык: Английский

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Artificial Intelligence in Disaster Management

Advances in environmental engineering and green technologies book series, Год журнала: 2025, Номер unknown, С. 73 - 114

Опубликована: Янв. 24, 2025

This chapter examines using artificial intelligence (AI) and deep learning (DL) in disaster management. It describes a paradigm shift towards proactive measures preventing managing natural disasters. Traditional, reactive methods often reach their limits. At the same time, AI-based approaches can improve early warning systems allocate resources more efficiently through analysis of large, heterogeneous data sets ability to recognize complex patterns. The article highlights application DL models, such as Convolutional Neural Networks (CNNs), analyze satellite imagery utility response. Both technical ethical challenges are discussed, particularly protection, bias, transparency models. Finally, framework is presented that provides guidelines for effective responsible use AI management promotes long-term sustainability fairness this area.

Язык: Английский

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Leveraging Social Media Data to Improve Disaster Response and Recovery Efforts Using Artificial Intelligence Techniques: A Comprehensive Review

Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 375 - 400

Опубликована: Янв. 1, 2025

Язык: Английский

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Identifying final demand points for aid in the aftermath of sudden-onset climate-related disasters in Peru: a supervised learning approach

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105593 - 105593

Опубликована: Май 1, 2025

Язык: Английский

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Real-time decision support model for logistics of emergency patient transfers from hospitals via an integrated optimisation and machine learning approach

Progress in Disaster Science, Год журнала: 2024, Номер unknown, С. 100397 - 100397

Опубликована: Дек. 1, 2024

Язык: Английский

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Developing a Digital Disaster Documents System for Essential Documents: Perspectives of Decision-Makers in Disaster and Emergency Management in Canada

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 114, С. 104975 - 104975

Опубликована: Ноя. 1, 2024

Язык: Английский

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Trends and Developments in the Use of Machine Learning for Disaster Management: A Bibliometric Analysis

IFIP advances in information and communication technology, Год журнала: 2023, Номер unknown, С. 92 - 104

Опубликована: Дек. 12, 2023

Язык: Английский

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