Applications of artificial intelligence for disaster management

W Sun, P Bocchini, BD Davison - Natural Hazards, 2020 - Springer
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

[HTML][HTML] Flying free: A research overview of deep learning in drone navigation autonomy

T Lee, S Mckeever, J Courtney - Drones, 2021 - mdpi.com
Drones | Free Full-Text | Flying Free: A Research Overview of Deep Learning in Drone
Navigation Autonomy Next Article in Journal Unmanned Autogyro for Mars Exploration: A …

A survey on UAV computing platforms: A hardware reliability perspective

F Ahmed, M Jenihhin - Sensors, 2022 - mdpi.com
This study describes the Computing Platforms (CPs) and the hardware reliability issues of
Unmanned Aerial Vehicles (UAVs), or drones, which recently attracted significant attention …

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney, Melbourne and Brisbane

N Kankanamge, T Yigitcanlar, A Goonetilleke - Telematics and Informatics, 2021 - Elsevier
In recent years, artificial intelligence (AI) is being increasingly utilised in disaster
management activities. The public is engaged with AI in various ways in these activities. For …

The development of new remote technologies in disaster medicine education: a scoping review

CL Kao, LC Chien, MC Wang, JS Tang… - Frontiers in public …, 2023 - frontiersin.org
Background Remote teaching and online learning have significantly changed the
responsiveness and accessibility after the COVID-19 pandemic. Disaster medicine (DM) has …

Training a disaster victim detection network for UAV search and rescue using harmonious composite images

N Zhang, F Nex, G Vosselman, N Kerle - Remote Sensing, 2022 - mdpi.com
Human detection in images using deep learning has been a popular research topic in recent
years and has achieved remarkable performance. Training a human detection network is …

Natural disasters intensity analysis and classification based on multispectral images using multi-layered deep convolutional neural network

M Aamir, T Ali, M Irfan, A Shaf, MZ Azam, A Glowacz… - Sensors, 2021 - mdpi.com
Natural disasters not only disturb the human ecological system but also destroy the
properties and critical infrastructures of human societies and even lead to permanent …

An Optimized Multi-Task Learning Model for Disaster Classification and Victim Detection in Federated Learning Environments

YJ Wong, ML Tham, BH Kwan, EMA Gnanamuthu… - IEEE …, 2022 - ieeexplore.ieee.org
Disaster classification and victim detection are two important tasks in enabling efficient
rescue operations. In this paper, we propose a multi-task learning (MTL) model which …

Transforming ground disaster response: Recent technological advances, challenges, and future trends for rapid and accurate real-world applications of survivor …

AJ Soto-Vergel, JC Velez, R Amaya-Mier… - International Journal of …, 2023 - Elsevier
Recent technological advancements, encompassing cutting-edge sensors, drones, and AI
systems, present novel prospects for enhancing survivor detection in disaster scenarios …

A study for detecting disaster victims using multi-copter drone with a thermographic camera and image object recognition by SSD

W Hoshino, J Seo, Y Yamazaki - 2021 IEEE/ASME …, 2021 - ieeexplore.ieee.org
It is dangerous for people to approach a building damaged by an earthquake when there is
a risk of it collapsing, and the likelihood of survival of victims of building collapse decreases …