Well, this is what a Cape Town based software and solution developer, Solution House Software, claim they can do. They are using artificial intelligence to predict when and where crime is going to happen.
ITNewsAfrica reports on Solution House Software’s recently announced artificial intelligence (AI) module for Incident Desk, a program that will predict and map potential crimes,.
According to Solution House Software director, Tiaan Janse van Rensburg, the Incident Desk Predictive Analysis module will initially focus solely on crime. Future versions may be expanded to include other industries such as facility management and maintenance. The early narrow focus will allow the system to achieve better results and hone the AI engine even further before it will be applied to other incident management areas.”
Incident Desk uses a multi-tenant model, which combines numerous customer areas, properties and buildings into one solution. This includes urban areas, central improvement districts, neighbourhood watch initiatives, estates, shopping malls and even schools.
“Because Incident Desk is built on a multi-tenant model, it allows us to develop this type of technology and make it available affordably across the user base,” says Janse van Rensburg. “The other advantage is that, because we’re multi-tenant at almost every site, we get to use many different data feeds that makes this type of technology much more predictable and accurate.
One of the biggest problems currently plaguing public safety and security are the ‘islands of data’ that are not being shared or centralised, which makes it difficult to data mine and analyse.
The Incident Desk Predictive Analysis module uses machine learning technology developed by Solution House together with aggregated data from multiple information sources to determine the likelihood of different types of criminal activity in the Incident Desk management area.
“With the module installed, Incident Desk generates 7 and 30-day forecasts as heat maps based on crime types and incident probabilities that managers can use to optimise their finite security resources,” says Janse van Rensburg.
“Crime is notoriously difficult to predict, but given that Incident Desk can access so many different types of data – including weather patterns and forecasts and historical data – the results are based on fairly accurate and proven trending algorithms,” her says.
“What’s more, the technology we developed is self-learning, which means Incident Desk continuously reviews, corrects and refines its predictions. That means that, over time, results will necessarily become more accurate, to the point where we hope that managers can resource themselves correctly and prevent or eliminate certain types of crime entirely from their areas.”
