Transitioning fire departments into data-driven organizations is critical to improving public safety. This project addresses barriers that departments face when making this transition and demonstrates how our team has accelerated this process for departments across the country. Our research has seen the following impacts:
Principle Investigator: Tyler Garner
Public Safety Organizations are finding it increasingly difficult to balance limited resources while simultaneously justifying current operations and adapting to changing service demands. By effectively analyzing and visualizing data, public safety organizations can proactively monitor changing response landscapes and make data driven decisions while objectively monitoring the outcome. This can impact all aspects of a public safety organization including staffing levels, development of standard operating procedures and internal policies, training efforts, and resource deployments. Although it is hard to deny the potential impact of data analytics in the public safety sector, analyzing and visualizing data is not an easy feat given the constraints of many public safety organizations.
Today, effective data exploitation requires software licenses, specialized knowledge of tools, and in-house technical expertise that public safety organizations often lack. Larger organizations utilize commercial off-the-shelf tools that are cost prohibitive for small and medium size organizations. Furthermore, proprietary tools end up vendor locking the customer, reducing an organization's ability to adapt. This project will enable wide scale utilization of powerful real-time data analytics for public safety organizations by producing an open source analytics platform, called StatEngine, built from "best-of-breed" data analysis and visualization tools.
Objectives of StatEngine include:
StatEngine will accelerate public safety adoption of data analytics by eliminating common barriers of entry including cost and technical expertise. Once complete, public safety organizations of any size will be able to exploit large volumes of complex, highly relevant, and impactful data sets in real time.
To learn more about StatEngine, visit our website, GitHub, or follow us on twitter.