Gotham is an Alexa-based tool that maps a novel real-time safety index

Underwriter Laboratories Winner

Is it safe to walk to P.F. Chang’s tonight? Gotham is a conversational Alexa skill that provides a seamless safety index heat-map based on geographical parameters collected from OpenData and continuous feedback given by the community. The OpenData parameters include outstanding arrest warrants, Las Vegas police calls for service, and code enforcement.

We made this project because we saw how much of an impact real-time street level safety data can have in a person’s life. For some people walking around at night, or even to their car, it is considered a team effort. Gotham enables full and exact communication of known threats to empower a newly informed citizenry with smart decision making ability. Moreover, Gotham offers real-time feedback to governments that can dynamically improve operations and thus improve the threat landscape itself, minimizing community risk. Governments can take easy action because there is support from a streaming feed of individual involvement. Gotham will directly let us know who to contact in the city to solve a problem, and civic engagement leads to heightened municipal responsiveness.

You can say things like “Show me the Venetian” and you’ll be instantly shown a real-time safety index map of the immediate area surrounding the Venetian. This relative real-time safety index is updated daily, and it is set on a range of 0 to 100. In addition to using existing OpenData, Gotham determines the relative safety index values at each point in the city map based on continuous safety feedback given by community members. This allows community members to file their own feedback, which will be added to the map and sent to the respective authority on the matter to be taken care of. This feedback dashboard feature will allow cities to categorize departments that require the most attention.

Severity weighting is then assigned to each feedback and crime within the city based on textual analysis. Finally, the safety index at a point is calculated by summing the points distance from nearby feedbacks and crimes and multiplying each of these feedbacks/crimes by their respective severity weighting.