Generation of the last forecasts: 20 April 2021 17:41:11 (UTC)
This model provides the prediction of the probability of emergency calls for medical purporse to the Fire Department of the City of San Francisco. It is based on records received by the SFFD. This database is combined with atmospheric, calendar and additional data to produce forecasts of the probability that a call occurs in the coming hour for a 7-days period. The results are displayed on Google Maps from green for low probabilities to red for high probabilities.
The map is initially displayed with the current prediction (at San Francisco local time) of the probabilities of calls for medical incidents and is automatically refreshed every hour. Use the timeline bar (below the map) or the time control panel (on the map) to get a forecast at any other available time.
You can also change the region by moving on the map, change the scale or the background settings.
The minimum and maximum values of the probabilities are initially displayed on the map. You can display the forecast at any other place by directly clicking on the map. Use the button "Remove all markers" to delete all the displayed probabilities.
This project uses the "Fire Department Calls for Service" dataset (see below for details). These calls for service counts are combined with calendar and weather data from various models. Artificial intelligence and machine learning techniques are then used to build predictive models and forecasts for future calls probabilities.
All the data are provided by the San Francisco Fire Department and are available at this link under the Open Data Commons Public Domain Dedication and License.
All the data generated by this experimental model are freely available without warranty of any kind.