Crime risk forecasting

Abstract

A computer-based crime risk forecasting system and corresponding method are provided for generating crime risk forecasts and conveying the forecasts to a user. With the conveyed forecasts, the user can more effectively gauge both the level of increased crime threat and its potential duration. The user can then leverage the information conveyed by the forecasts to take a more proactive approach to law enforcement in the affected areas during the period of increased crime threat.

1 . A computing system, comprising:
 one or more processors;   storage media;   one or more programs stored in the storage media and configured for execution by the one or more processors, the one or more programs comprising instructions configured for:   storing crime incident data reflecting crime incidents that occur over a period of time;   based, at least in part, on the crime incident data, predicting a crime risk for a geographic area, a time window, and a crime type;   wherein the time window is in the future relative to the period of time over which the crime incidents occur;   generating and displaying a graphical user interface overlay on an interactive geospatial basemap;   wherein the interactive geospatial basemap is generated by a geospatial application; and   wherein the graphical user interface overlay visually indicates at least all of:
 the geographic area, 
 the time window, 
 the crime type, 
 the crime risk, and 
 a number of the crime incidents that at least occur in the geographic area over the period of time during a periodically recurring continuous period of time. 
   
     
     
         2 . The system of  claim 1 , wherein:
 the periodically recurring continuous period of time is a day of the week, the week having seven days of which the day is one;   the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time is a number of the crime incidents that at least occur in the geographic area over the period of time on the day of the week.   
     
     
         3 . The system of  claim 1 , wherein:
 the periodically recurring continuous period of time is an hour of the day, the day having 24 hours of which the hour is one;   the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time is a number of the crime incidents that at least occur in the geographic area over the period of time on the hour of the day.   
     
     
         4 . The system of  claim 1 , wherein each of the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time are of the crime type. 
     
     
         5 . The system of  claim 1 , wherein one or more of the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time are not of the crime type. 
     
     
         6 . The system of  claim 1 , wherein:
 the time window corresponds to a law enforcement patrol shift on a particular day; and   the graphical user interface overlay visually indicates the particular day and a time of the law enforcement patrol shift on the particular day.   
     
     
         7 . tem of  claim 1 , wherein the instructions are further configured for:
 generating a weighted sum of a plurality of crime incidents, of the crime incidents, within a space threshold and a time threshold; and   wherein the predicting the crime risk is based, at least in part, on the weighted sum.   
     
     
         8 . The system of  claim 1 , wherein the instructions are further configured for:
 generating a sum of a plurality of crime incidents, of the crime incidents, that occurred in the geographic area; and   wherein the predicting the crime risk is based, at least in part, on the sum.   
     
     
         9 . The system of  claim 1 , wherein the instructions are further configured for:
 obtaining global positioning system (GPS) information from radio equipment used by law enforcement officers patrolling at least the geographic area;   determining a level of law enforcement patrol presence for at least the geographic area based, at least in part, on the GPS information; and   wherein the predicting the crime risk is based, at least in part, on the level of law enforcement patrol presence for at least the geographic area.   
     
     
         10 . The system of  claim 1 , wherein the instructions are further configured for:
 obtaining computer-aided dispatch data reflecting crime type, crime date, and crime location of one or more of the crime incidents;   wherein the crime incident data comprises the computer-aided dispatch data; and   wherein the predicting the crime risk is based, at least in part, on the computer-aided dispatch data.   
     
     
         11 . A method performed by a computing system comprising one or more processors and storage media, the method comprising:
 storing crime incident data reflecting crime incidents that occur over a period of time;   based, at least in part, on the crime incident data, predicting a crime risk for a geographic area, a time window, and a crime type;   wherein the time window is in the future relative to the period of time over which the crime incidents occur;   generating and displaying a graphical user interface overlay on an interactive geospatial basemap;   wherein the interactive geospatial basemap is generated by a geospatial application; and   wherein the graphical user interface overlay visually indicates at least all of:
 the geographic area, 
 the time window, 
 the crime type, 
 the crime risk, and 
 a number of the crime incidents that at least occur in the geographic area over the period of time during a periodically recurring continuous period of time. 
   
     
     
         12 . The method of  claim 11 , wherein:
 the periodically recurring continuous period of time is a day of the week, the week having seven days of which the day is one;   the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time is a number of the crime incidents that at least occur in the geographic area over the period of time on the day of the week.   
     
     
         13 . The method of  claim 11 , wherein:
 the periodically recurring continuous period of time is an hour of the day, the day having 24 hours of which the hour is one;   the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time is a number of the crime incidents that at least occur in the geographic area over the period of time on the hour of the day.   
     
     
         14 . The method of  claim 11 , wherein each of the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time are of the crime type. 
     
     
         15 . The method of  claim 11 , wherein one or more of the number of the crime incidents that at least occur in the geographic area over the period of time during the periodically recurring continuous period of time are not of the crime type. 
     
     
         16 . The method of  claim 11 , wherein:
 the time window corresponds to a law enforcement patrol shift on a particular day; and   the graphical user interface overlay visually indicates the particular day and a time of the law enforcement patrol shift on the particular day.   
     
     
         17 . The method of  claim 11 , further comprising:
 generating a weighted sum of a plurality of crime incidents, of the crime incidents, within a space threshold and a time threshold; and   wherein the predicting the crime risk is based, at least in part, on the weighted sum.   
     
     
         18 . The method of  claim 11 , further comprising:
 generating a sum of a plurality of crime incidents, of the crime incidents, that occurred in the geographic area; and   wherein the predicting the crime risk is based, at least in part, on the sum.   
     
     
         19 . The method of  claim 11 , further comprising:
 obtaining global positioning system (GPS) information from radio equipment used by law enforcement officers patrolling at least the geographic area;   determining a level of law enforcement patrol presence for at least the geographic area based, at least in part, on the GPS information; and   wherein the predicting the crime risk is based, at least in part, on the level of law enforcement patrol presence for at least the geographic area.   
     
     
         20 . The method of  claim 11 , wherein the instructions are further configured for:
 obtaining computer-aided dispatch data reflecting crime type, crime date, and crime location of one or more of the crime incidents;   wherein the crime incident data comprises the computer-aided dispatch data; and   wherein the predicting the crime risk is based, at least in part, on the computer-aided dispatch data.