Public Emergency

Public emergency response research focuses on improving the speed and effectiveness of crisis management through advanced technologies. Current efforts concentrate on developing predictive models using statistical and machine learning techniques, including negative binomial regression and graph neural networks, to anticipate events like fires and disease outbreaks, and leveraging large language models to process emergency information from various sources, such as social media and 911 calls. These advancements aim to optimize resource allocation, enhance communication, and improve the delivery of aid, particularly in remote or underserved areas, potentially using innovative technologies like low-cost robotic delivery systems. The ultimate goal is to mitigate the impact of emergencies and improve overall community resilience.

Papers

March 28, 2024

Information Cascade Prediction under Public Emergencies: A Survey
Qi Zhang, Guang Wang, Li Lin, Kaiwen Xia, Shuai Wang
Timely Survey Human Prediction Information Cascade Public Emergency

February 14, 2024

Statistical and Machine Learning Models for Predicting Fire and Other Emergency Events
Dilli Prasad Sharma, Nasim Beigi-Mohammadi, Hongxiang Geng, Dawn Dixon, Rob Madro, Phil Emmenegger, Carlos Tobar, Jeff Li, Alberto Leon-Garcia
Machine Learning Model Predictive Model Prediction Model Wildfire Prediction Public Emergency Event Prediction Method

February 3, 2024

Emergency Computing: An Adaptive Collaborative Inference Method Based on Hierarchical Reinforcement Learning
Weiqi Fu, Lianming Xu, Xin Wu, Li Wang, Aiguo Fei
Hierarchical Reinforcement Learning Disaster Response Collaborative Inference Public Emergency

January 12, 2024

LLM-Assisted Crisis Management: Building Advanced LLM Platforms for Effective Emergency Response and Public Collaboration
Hakan T. Otal, M. Abdullah Canbaz
Language Model Natural Language Processing Disaster Response LLM Assisted Decision Making Emergency Response Public Emergency

September 13, 2023

A Novel Low-Cost, Recyclable, Easy-to-Build Robot Blimp For Transporting Supplies in Hard-to-Reach Locations
Karen Li, Shuhang Hou, Matyas Negash, Jiawei Xu, Edward Jeffs, Diego S. D'Antonio, David Saldaña
Various Fast Moving Drone Long Form Novel Low Cost Rural Connectivity Lead Time Robotic Blimp Public Emergency

October 24, 2022

Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNs
Muhammed Fatih Balın, Ümit V. Çatalyürek
Graph Neural Network Neighbor Sampling Public Emergency

Public Emergency

Papers

Information Cascade Prediction under Public Emergencies: A Survey

Statistical and Machine Learning Models for Predicting Fire and Other Emergency Events

Emergency Computing: An Adaptive Collaborative Inference Method Based on Hierarchical Reinforcement Learning

LLM-Assisted Crisis Management: Building Advanced LLM Platforms for Effective Emergency Response and Public Collaboration

A Novel Low-Cost, Recyclable, Easy-to-Build Robot Blimp For Transporting Supplies in Hard-to-Reach Locations

Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNs