AI for Smart Disaster Resilience among Communities DOI

Amirulikhsan Zolkafli,

Nur Suhaili Mansor,

Mazni Omar

et al.

Studies in systems, decision and control, Journal Year: 2024, Volume and Issue: unknown, P. 369 - 395

Published: Jan. 1, 2024

Language: Английский

A decision-making tool for the determination of the distribution center location in a humanitarian logistics network DOI
Xenofon Taouktsis, Christos Zikopoulos

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 122010 - 122010

Published: Oct. 9, 2023

Language: Английский

Citations

14
Efficient offloading in disaster-affected areas using unmanned aerial vehicle-assisted mobile edge computing: A gravitational search algorithm-based approach DOI
Santanu Ghosh, Pratyay Kuila

International Journal of Disaster Risk Reduction, Journal Year: 2023, Volume and Issue: 97, P. 104067 - 104067

Published: Oct. 1, 2023

Language: Английский

Citations

12
Strategies for Humanitarian Logistics and Supply Chain in Organizational Contexts: Pre- and Post-Disaster Management Perspectives DOI Creative Commons
Amir Aghsami, Simintaj Sharififar, Nader Markazi Moghaddam

et al.

Systems, Journal Year: 2024, Volume and Issue: 12(6), P. 215 - 215

Published: June 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.

Language: Английский

Citations

4
Artificial Intelligence in Disaster Management DOI
Silvio Andrae

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 73 - 114

Published: Jan. 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.

Language: Английский

Citations

0
Harnessing Mobile Technology for Flood Disaster Readiness and Response: A Comprehensive Review of Mobile Applications on the Google Play Store DOI Creative Commons
Nuwani Kangana, Nayomi Kankanamge, Chathura De Silva

et al.

Urban Science, Journal Year: 2025, Volume and Issue: 9(4), P. 106 - 106

Published: April 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.

Language: Английский

Citations

0
Leveraging Social Media Data to Improve Disaster Response and Recovery Efforts Using Artificial Intelligence Techniques: A Comprehensive Review DOI

Shilpa P. Pimpalkar,

Madhavi Devaraj

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 375 - 400

Published: Jan. 1, 2025

Language: Английский

Citations

0
Real-time decision support model for logistics of emergency patient transfers from hospitals via an integrated optimisation and machine learning approach DOI Creative Commons
Maziar Yazdani,

Siroos Shahriari,

Milad Haghani

et al.

Progress in Disaster Science, Journal Year: 2024, Volume and Issue: unknown, P. 100397 - 100397

Published: Dec. 1, 2024

Language: Английский

Citations

2
Developing a Digital Disaster Documents System for Essential Documents: Perspectives of Decision-Makers in Disaster and Emergency Management in Canada DOI Creative Commons
Mahed-Ul-Islam Choudhury, Evalyna Bogdan, Julie Drolet

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 114, P. 104975 - 104975

Published: Nov. 1, 2024

Language: Английский

Citations

1
Trends and Developments in the Use of Machine Learning for Disaster Management: A Bibliometric Analysis DOI
Kudakwashe Maguraushe, Patrick Ndayizigamiye, Tebogo Bokaba

et al.

IFIP advances in information and communication technology, Journal Year: 2023, Volume and Issue: unknown, P. 92 - 104

Published: Dec. 12, 2023

Language: Английский

Citations

2
AI for Smart Disaster Resilience among Communities DOI

Amirulikhsan Zolkafli,

Nur Suhaili Mansor,

Mazni Omar

et al.

Studies in systems, decision and control, Journal Year: 2024, Volume and Issue: unknown, P. 369 - 395

Published: Jan. 1, 2024

Language: Английский

Citations

0