This approach provides increased visibility of crucial information, such as crime hotspots, to not only reach government targets and make the data more available to the public, but also to put preventative procedures in place to help fight and reduce crime.
The demand for more detailed, accurate information has grown. Police forces are beginning to realise they can access and analyse their data, be it real-time or even location-based to help prevent and reduce crime.
With the advent of more accessible and flexible web-based data analytics, stored data can now be combined with real-time data in the field, allowing for analysis of law enforcement data.
By implementing a combination of techniques such as data mining, web-based predictive analytics and business intelligence (BI) tools, forces are improving the accuracy of their location-based information and delivering increased visibility of crime figures through easy-to-use charts and graphs held on a common online platform.
Accurately pinpointing crime
By marrying BI with a geographic information system (GIS) and mapping capabilities, information can be analysed online to take full advantage of its geo-spatial parts, such as street names, postcodes and telephone numbers.
In the law enforcement sector, this software can then be applied to accurately pinpoint known offenders and analyse their criminal behavioural patterns in order to determine when they are likely to commit a crime.
The system can accurately forecast the likelihood of crimes in specific areas by correlating present and past information like criminal records, motive and type of crime at a specific location against certain variables such as weather, particular days of the week and major events happening in the location.
This type of deployment enables police forces to make smarter decisions about the deployment of resources to reduce crime enabling patrol cars to be deployed to high-risk areas to prevent these crimes from happening and catch those known offenders in the act. As a result of implementing these technologies certain police forces have found that crime in their area decreased by 49 per cent.
Accident prevention
Additionally, web-based data analytics can help determine accident black spots. When a road accident occurs, it is logged and stored on a central system. The system will then automatically collate real-time and historical data, enabling the police to analyse accidents in the same area through the business intelligence software.
The police can then use this data to determine whether certain so-called accident-prone areas need a higher degree of policing. They can also make more informed decisions on whether road layouts would benefit from being revised or even whether a particular set of traffic lights are causing reoccurring problems.
Using technology in this way can lead to big improvements in road safety, reducing the number of road accidents, meet government targets and ultimately to save lives.
Improved crowd control
The police can also apply this technology to analyse large events such as football matches to improve crowd control procedures. This uses historical data about where the majority of spectators are located during matches, both in the stadium, around the grounds and at train, bus and tube stops.
This is particularly important considering the popularity of festivals, sporting events and music concerts, where tens of thousands of people travel to one place at the same time. If these live events have been analysed previously and this information is then matched with real-time data, police can deploy appropriate resources to ensure the public is monitored and kept safe.
The use of location-based technology in police forces brings about clear benefits such as improving the allocation of resources by better understanding and analysing variables that can influence crimes and accidents in certain areas. These solutions assist the police in preventing and reducing crime, keeping communities safer.
Technology allows police forces to deliver clear and accurate data to the government when necessary to meet public sector targets. The implementation of technologies such as mobile BI, business intelligence and predictive analytics should become more and more widespread since the benefits of these solutions have been proven to improve public safety and reduce crime.
