# Designing Decision Support Systems for Emergency Response: Challenges and Opportunities

arXiv: https://arxiv.org/abs/2202.11268 · HTML: https://mlsanity.com/paper/2202.11268/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 43 references that are in the map.
- First posted on arXiv 23 Feb 2022.

## Builds on (most cited first, 13 of 13)

- [MIPaaL: Mixed Integer Program as a Layer](https://mlsanity.com/paper/1907.05912/) (2019)
- [Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving](https://mlsanity.com/paper/1905.02680/) (2019)
- [Neural Approximate Dynamic Programming for On-Demand Ride-Pooling](https://mlsanity.com/paper/1911.08842/) (2019)
- [Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges](https://mlsanity.com/paper/1511.03010/) (2015)
- [A Review of Incident Prediction, Resource Allocation, and Dispatch Models for Emergency Management](https://mlsanity.com/paper/2006.04200/) (2020)
- [Hierarchical Planning for Resource Allocation in Emergency Response Systems](https://mlsanity.com/paper/2012.13300/) (2020)
- [An Online Decision-Theoretic Pipeline for Responder Dispatch](https://mlsanity.com/paper/1902.08274/) (2019)
- [Online Scheduling of a Residential Microgrid via Monte-Carlo Tree Search and a Learned Model](https://mlsanity.com/paper/2005.06161/) (2020)
- [On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities](https://mlsanity.com/paper/2001.07362/) (2020)
- [Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems](https://mlsanity.com/paper/2106.08307/) (2021)
- [Uncertainty Aware Wildfire Management](https://mlsanity.com/paper/2010.07915/) (2020)
- [Practitioner-Centric Approach for Early Incident Detection Using Crowdsourced Data for Emergency Services](https://mlsanity.com/paper/2112.02012/) (2021)
- [Emergency Incident Detection from Crowdsourced Waze Data using Bayesian Information Fusion](https://mlsanity.com/paper/2011.05440/) (2020)

## Built on by (most cited first, 1 of 1)

- [Generative Anomaly Detection for Time Series Datasets](https://mlsanity.com/paper/2206.14597/) (2022)

## Abstract (arXiv)

Designing effective emergency response management (ERM) systems to respond to incidents such as road accidents is a major problem faced by communities. In addition to responding to frequent incidents each day (about 240 million emergency medical services calls and over 5 million road accidents in the US each year), these systems also support response during natural hazards. Recently, there has been a consistent interest in building decision support and optimization tools that can help emergency responders provide more efficient and effective response. This includes a number of principled subsystems that implement early incident detection, incident likelihood forecasting and strategic resource allocation and dispatch policies. In this paper, we highlight the key challenges and provide an overview of the approach developed by our team in collaboration with our community partners.