1.0 Introduction - WayneWang86/UDistrict-Real-Time-Fire-Response GitHub Wiki

1.1 Problem Situation:

The setting for our problem is that fire department members and officials want to improve their ability to quickly dispatch to reported emergencies. The data can also assist business owners by heightening awareness of possible incidents with knowledge on when and where certain incidents are more likely to occur. People who live, travel and commute around the U-District may also want to acquire information about the level of safety regarding fire incidents. The main stakeholders are the fire department employees, officials, businesses, and individuals who live or frequently commute within the fire department’s response territory.

However, when there are multiple incidents occurring simultaneously there is tension between limited fire department resources and individuals in need. Ethically it may be dangerous to prioritize the larger society's safety over the individual. While fire departments may want to prioritize being able to quickly dispatch to high-risk areas, it should not come at the expense of others' ability to receive aid.

The general issues at stake are fire departments cannot utilize their resources to be as prepared as possible for any possible incidents. It is likely that certain areas are more or less prone to emergencies and require different levels of attention from the fire department. There is a policy that “the Seattle Fire Department provides a system for the dispatching of appropriate equipment to satisfactorily resolve reported emergencies”, showing the fire department's goal is to efficiently respond to emergencies. A data-driven approach will be a means to this end.

By building upon the API provided by the City of Seattle with data by the Seattle Fire Department we can create a visually accessible model that can help the Fire Department, businesses, and citizens to be more prepared.

1.2 What is the problem?

With the unpredictability of fire calls, it is hard for fire department members and officials to predict when they will receive calls and where the incident will occur. This has the potential to delay incident response times, especially when experiencing a high volume of calls. Civilians who live in this area are directly affected by how well the fire department responds, and more cautious citizens may use the information in planning where they spend their time. Businesses may lack awareness on what types of emergencies they should be wary of and try to prevent.

1.3 Why does it matter?

If fire department members and officials use organized information on fire calls they can predict which locations are of higher risk and pay more attention to that location, thus improving their ability to respond to emergency situations as soon as possible. If people who live in and travel around the area acquire organized information of fire calls, they can use caution in specific locations and timely adjust their living plans to improve their safety. Businesses can plan around times of year when certain issues are more prevalent and stop preventable emergencies from occurring.

1.4 How it will be addressed?

We plan to create data visualizations that show the distribution of fire calls in the U-District area, such as the number of fire calls received, locations of fire calls, and frequency of fire calls at different times of the year. We also plan to visualize how the frequency of different categories of reported incidents has changed over time.

Our primary audience is the fire department and officials who plan how units are dispatched. Specifically, we use a heatmap to visually encode the U-District and where incidents are most frequent at various times of the year. We also use a histogram to show the most common types of fire calls and how this has shifted over time.