{"id":633002,"date":"2024-12-18T20:32:17","date_gmt":"2024-12-19T01:32:17","guid":{"rendered":"https:\/\/www.rochester.edu\/newscenter\/?p=633002"},"modified":"2025-09-18T10:35:43","modified_gmt":"2025-09-18T14:35:43","slug":"data-science-rochester-fire-department-emergency-responses-633002","status":"publish","type":"post","link":"https:\/\/www.rochester.edu\/newscenter\/data-science-rochester-fire-department-emergency-responses-633002\/","title":{"rendered":"Data science students help speed up Rochester Fire Department\u2019s emergency responses"},"content":{"rendered":"

The students analyzed millions of data points to determine where to best place fire stations, fire trucks, and other resources.<\/strong><\/h2>\n

Where should the Rochester Fire Department (RFD) locate fire stations over the next 10 years to minimize response times to emergencies? Where should it deploy the most fire trucks? How do seasonal shifts impact the nature and volume of emergencies that firefighters need to respond to?<\/p>\n

These are questions that a team of students from the University of Rochester\u2019s<\/a> Goergen Institute for Data Science and Artificial Intelligence<\/a> explored over the course of a semester for their capstone project sponsored<\/a> by the RFD.<\/p>\n

\u201cWe were looking for someone from the outside to come in and provide a different set of ideas, experiences, and viewpoints to help us enhance our emergency response services,\u201d says Daniel Curran, a captain for planning and research who is responsible for technology-based projects at the RFD. \u201cWe felt the students would have an unbiased perspective and look at the situation and tell us, \u2018This is where the data leads us,\u2019 and come to their own conclusions.\u201d<\/p>\n

Over the course of the semester, the students used artificial intelligence and other data analytics tools to make sense of more than 1.6 million points of data collected by RFD from 2006 to 2024. They also incorporated external census data related to population, income, property, and housing to enrich their analysis.<\/p>\n

\u201cThis was an amazing opportunity to contribute something meaningful,\u201d says data science graduate\u00a0student<\/a> Brynn (Ye In) Lee \u201924 (MS). \u201cThe RFD has 15 fire stations, they\u2019re supporting about 500 personnel, and they have around 50,000 annual dispatches, so that\u2019s a huge impact that we can have on the community.\u201d<\/p>\n

The students developed interactive maps that allow the RFD to analyze how long it takes the firefighters to reach an incident, while providing information about the distribution of incidents across the city and the ability to sort by incident type. They also created models to predict the monthly incident density over the next 10 years for all 15 fire stations.<\/p>\n

In their analysis, the students found that the RFD is already effective at responding to incidents in a timely fashion. However, the students offered recommendations for small improvements that could further decrease response times. Their suggestions include reallocating specific types of trucks from one station to another and introducing programs similar to those in other cities that can address non-life-threatening calls with fewer resources.<\/p>\n

\"Diptych
FIRE ENGINE OF INNOVATION:<\/strong> To gain an appreciation for the firefighters\u2019 day-to-day responsibilities, each University of Rochester data science student, including Medhini Sridharr (center), completed a \u201cride-along\u201d with Engine 16.<\/figcaption><\/figure>\n

According to the students, a critical aspect to their project\u2019s success was going on \u201cride-alongs\u201d with the RFD, which gave them an appreciation for the firefighters\u2019 day-to-day responsibilities. They said witnessing the types of incidents the firefighters respond to, learning about their shifts, and seeing the equipment in person was enlightening.<\/p>\n

\u201cI used to think the fire department only deals with fire-related emergencies, but they deal with so many medical emergencies and spend a lot of time early in the morning patrolling their area to look for fire hazards,\u201d says Homayra Tabassum \u201924 (MS). \u201cGetting to see that in person helped us be much more insightful when we were thinking about resource allocation.\u201d<\/p>\n

The students said their weekly meetings with the RFD sponsors and collaborating with RFD\u2019s internal data analysts were important learning opportunities as well.<\/p>\n

\u201cDealing with real-world data is not always clean or exactly the way you want it, so the captain and the senior data analysts were extremely helpful,\u201d says team member Medhini Sridharr \u201924 (MS). \u201cThey helped us choose the most important variables based on their domain knowledge, which was crucial because we had more than 300 variables to consider. They helped us drill down to what\u2019s important.\u201d<\/p>\n

Overall, the students said they loved the chance to do a hands-on project with real-world implications, witness the firefighters at work first-hand, and deliver a product that will serve the RFD and local community for years to come.<\/p>\n

The project team included data science master\u2019s students Eugene Ayonga \u201924, Lee, Sridharr, Tabassum, as well as undergraduate data science<\/a> student Nour Assili \u201926.<\/p>\n","protected":false},"excerpt":{"rendered":"

The students analyzed millions of data points to determine where to best place fire stations, fire trucks, and other resources.<\/p>\n","protected":false},"author":1242,"featured_media":633032,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[9],"tags":[24292,38462,40082,37452,25592,18632],"class_list":["post-633002","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-campus-community","tag-artificial-intelligence","tag-class-of-2024","tag-class-of-2026","tag-community-engagement","tag-goergen-institute-for-data-science-and-artificial-intelligence","tag-hajim-school-of-engineering-and-applied-sciences"],"acf":[],"yoast_head":"\nData science students help speed up Rochester Fire Department\u2019s emergency responses<\/title>\n<meta name=\"description\" content=\"University of Rochester students analyzed millions of data points to determine 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