Application Integration

Making 911 Data Real Time

911 data realtimeWe are doing a lot of research on open data at the city level, here at Streamdata.io. We are interested in the future of cities, and enjoy some of the conversations around the concept of the “smart city”. To help invest in this area we are spending time studying the current state of city-level public data, and how it is currently gathered, stored, aggregated, and made available. This week we are looking into 911 data, and how this data is made available to the public on the web and via feeds.

When you are looking for open data, you can find a number of websites that provide real time, or near real time listings of 911 incidents:

Oneida Count, NY
Monroe County, NY
– Lancaster County, PA
– York Count, PA
– New Castle County, DE
– Thurston Count, WA

Some of the 911 agencies, and websites even have RSS feeds for them:

Lancaster County, PA
– Monroe County, NY
– Montgomery County, PA

You can also find some official 911 accounts on Twitter:

Ulster County, NY
– Saint Louis, MO
– Wake County, NC
– Bartholomew County, IN
– Duxbury, MA

However, there are only a handful of cities with public data feeds of their 911 data that are updated on a real time or near real time basis:

Seattle
– Baltimore
– Los Angeles
– San Francisco
– Dallas
– Detroit

This demonstrates a pretty big opportunity for working with 911 centers to get data published via a real time feed. This data is something that could be scraped, and aggregated from across the available websites. You could also take the audio feeds for 911 police radio, and translate into text, and make available via feeds. However, it really is something that should coming from an authoritative source, in a machine readable format, available in real-time. The challenge will be getting cash-strapped police agencies to invest in this type of technology, as well as the 911 system vendors on board with the concept–something that will take time.

There are many reasons why 911 data should be available in a real time machine readable feed as an API. We’ll explore those possibilities in future stories. Next up, we’ll be taking the handful of real time feeds here and proxying them through Streamdata.io to demonstrate what is possible. We have some partners who are doing interesting things with machine learning and artificial intelligence and are interested in real time municipal data to feed their models. Once we get a prototype up of 911 data streaming real time from Seattle, Baltimore, Los Angeles, San Francisco, Dallas, and Detroit we’ll publish another story about it showing what is possible when you take city data and make it real time in this way.

**Original source: streamdata.io blog