GIS and Analytics in the Fire Service

Based in the city of Vaughan with a population of more than 335,000, Vaughan Fire and Rescue Service (VFRS) strives to operate as efficiently and effectively as possible, while maintaining what is most important: the safety of firefighters and those who live in, work in and visit the city.

 

As a leader in the industry, it is VFRS’s responsibility to enhance its understanding of the needs of its growing city. The service seeks forward-looking analytic techniques to create greater value for citizens and the community through data-driven decision-making.

 

Setting the Direction

 

There is an increasing burden upon decision makers, such as city managers and fire chiefs, to demonstrate the efficiency of their services, and in the case of fire departments, to validate their performance. A persistent issue has been quantifying the level of fire risk and response challenges present in communities, taking life safety and property protection into consideration. The difficulty facing many communities is determining what “optimal” protection means from the standpoint of matching the limited resources of a community to its fire risk from a life safety and property protection standpoint.

 

In May 2019, VFRS developed a Master Fire Plan to set the direction of the service for the next 10 years. The detailed plan contains maps, charts and data; however, there were some gaps in using the data to fully understand the future development of the city and the resources required to keep pace. This problem indicated a need to develop tools that could properly determine and forecast operational capacity.

 

To address this issue, VFRS partnered with York Region, York University, the University of Calabria, Universidad Autónoma del Estado de México, and the University of Genoa to undertake a project in innovation that would:

· use shared data to create community profiles to understand risks within the city and the vulnerability index.

• map a future state of the municipality and current resources to develop predictive analytics.
• model and simulate VFRS’s response to emergencies to gain an in-depth analysis of response times and other key performance indicators.
• use data-driven, evidence-based decision-making to determine fire station locations and allocation of resources.

 

Using Data for the Future

 

Quantitative fire risk analysis is critical to the decision-making process required for resource allocation in mitigating the effects of fire. VFRS worked with its municipal partner, York Region, to learn about the techniques and tools that could drive insight from data. The difficulty was in gaining access to the various data sources, evaluating its accuracy, and then making sense of how it all fit together into a model. Ultimately, an interactive decision support tool was created. This was achieved by looking at historical response-time data, building permits, population data, present road networks and planned road extensions. From there, travel-time models for each fire station were generated using different scenarios. The response coverage for each scenario factored in the number of properties and population that could be reached as well as other key criteria, including vulnerable populations and areas that have been identified as difficult to access. The tool has become a vital resource and has helped VFRS make decisions about station placement, resource allocation and road network improvements.

 

Evaluating Performance through Simulation

 

For the second part of their project, VFRS partnered with York University’s Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM) team in the School of Administrative Studies, in collaboration with the Modelling and Simulation Center - Laboratory of Enterprise Solutions (MSC-LES) of the University of Calabria. This part was two-fold: to conduct a statistical analysis of the VFRS incident database (covering records since January 2009), and to undertake modelling and simulation of VFRS’s response to emergencies. VFRS sought to answer these questions:

• Is the current assignment of apparatus/crews operationally adequate and efficient?
• Is there a need to increase responding units at any station or to reallocate existing ones to other stations?
• Would it be appropriate for VFRS to consider building additional fire stations?

 

The modelling and simulation framework involved two different simulation models running on separate platforms: an Incident Generation Engine, which simulates the arrival to emergency incidents, and a Response Simulation Model, which is an agent-based simulation model that receives inputs from the first model.

 

The objective was to use modelling and simulation technology to evaluate the expected operating performance and efficiency of the VFRS system (stations, vehicles and firefighting crews), taking into consideration the uncertainties of emergencies (e.g. time and geographic location of the event, type of incident, alarm processing, vehicle turnout time and on-scene time, among other relevant variables).

 

Gaining Insight from Data

 

VFRS worked with York University for 18 months on the modelling and simulation. The service provided historical data and operational procedures/protocols, as well as reviewed the simulation model and preliminary results with the researchers and offered input into required adjustments. In particular, VFRS validated some of the basic assumptions made in the model and the initial simulation results. This enabled the researchers to better identify statistics and operational parameters to build and refine the model as needed.

 

Interpreting and using data is necessary for fire service management. Decisions on a wide range of critical issues, such as funding, apparatus purchases, station placement, and staffing, are validated using data obtained from a wide variety of sources. VFRS has developed predictive, spatial and prescriptive methods to segregate, organize and model the data to draw conclusions and identify patterns. They used math, statistics and modelling along with creativity and skepticism to ask the right questions, explore data and distill it down to insights that support their most critical decisions while reducing costs, improving efficiencies and mitigating risks.

 

The modelling and simulation tool was used to examine response performance. Results from the simulation have led VFRS to better evaluate community risks and consider improvements in its operations. The modelling has allowed VFRS to determine optimal unit availability and ideal station and truck placement to have a positive impact on response times, which can ultimately reduce property damage and save lives.

 

Award-Winning Work

 

The completed project, titled “Igniting Insight: Using Geographic Information Systems (GIS) and Analytics in the Fire Service,” received the bronze 2019 Innovative Management Award from the National Institute of Public Administration of Canada (IPAC). Launched in 1990, the Innovative Management Award recognizes government organizations that have shown exceptional innovations that address the wide variety of issues facing society today. It celebrates the ability of public servants across the country to transform public administration, advance knowledge of management systems and structures, and improve transparency, accountability and responsiveness while increasing public participation.

 

The simulation model received international attention when it was presented at the 9th International Defence and Homeland Security Simulation Workshop, in Lisbon, Portugal, September 2019 in a presentation titled “Agent-Based Simulation of a Fire Department’s Response to Emergency Incidents.” VFRS continues to collaborate with Dr. Asgary and Dr. Solis at York University on two new projects; including developing an artificial intelligence resource prediction system and a mixed reality fire simulation training and education tool.

 

Commitment to Innovation

 

Public service agencies, such as fire departments, are capitalizing on the synthesis of big data in an effort to enhance its capabilities as well as protect its personnel and the citizens it serves. VFRS’s use of data and smart technology aligns with the City of Vaughan’s overall commitment to innovation and continuous improvement. In January 2016, Vaughan became the second municipality in Canada to be World Council on City Data ISO 37120 Platinum Certified and will be the first city to pilot the new Smart Cities standard ISO 37122.

 

“Vaughan continues to elevate its reputation as a trusted and sought-after Smart City technology leader. We remain committed to working with Vaughan Fire and Rescue Service to develop innovative solutions that ultimately improve the human condition for all people,” says Hon. Maurizio Bevilacqua, Mayor, City of Vaughan.

 

Big data’s worth is realized only as much as the analytical insights derived from it to make decisions and take action. The success of this project lies in the ability for VFRS to use data to identify the impact of any resource allocation or infrastructure change on performance and response times – two factors that are paramount when responding to an emergency. Employing data analytics for fire prevention, suppression and response allocation will help ensure the fire service is strong, resilient and well-positioned for the future.

 

City of Vaughan, Vaughan Fire & Rescue Service

 

Deryn Rizzi, Fire Chief

Michael Ing, Assistant Deputy Chief

Andrea Alexander, Supervisor of Communications

Kevin Plested, Captain

Tamara Roitman, Firefighter

 

Regional Municipality of York - Analytics and Visualization; Data, Analytics and Visualization Services Branch

 

Duncan Rowe, Manager

Peter Chu Su, Data Scientist

Yishi Zhao, Data Scientist

Sarah Allen, GIS Technologist

 

University Researchers

 

Dr. Adriano O. Solis / Dr. Ali Asgary, School of Administrative Studies, York University

Dr. Jenaro Nosedal-Sánchez, Facultad de Ingeniería, Universidad Autónoma del Estado de México Cerro de Coatepec

Dr. Francesco Longo / Antonio Briga / Antonella Castagna, DIMEG, University of Calabria

Beatrice Zaccaro, DIME, University of Genoa