Predictive analytics systems use complex algorithms to leverage information from multiple system components and databases, giving security personnel a better picture of the operating environment.
One of the major concerns that law enforcement agencies have is that they are forced to play catchup with the criminals. Even when they work hard to control illegal activities in a specific area, criminals would pop up elsewhere. To solve this problem, a proactive approach like predictive analytics is necessary.
The objective of limiting the impact
According to Peter Matuchniak, CTO of
Maxxess Systems, the objective of all predictive security analytics tools is to prevent minor issues from escalating into major ones. The sooner you can act, the easier problems are to deal with.
“If you can design a solution that gives you more accurate data about significant events that are happening now – taking inputs from a wide range of systems and sources – you can compare that against what has happened in the past, and then you can start to anticipate problems,” Matuchniak said. “With predictive analytics, it’s important to remember that you can reduce risks in their widest sense by not just identifying obvious security breaches (alarm/triggers) but by anticipating issues that might affect day-to-day operational efficiency. The user can decide what those issues are, and clearly the larger the organization or entity being monitored, the more sophisticated the data handling will be.”
Leveraging disparate data
Today’s cities operate in highly dynamic environments that include
constantly-evolving threats. Staying one step ahead of these threats requires substantial effort on the part of security and emergency management teams to sift through the mountains of data, analyze trends and make the correct decisions at the right time.
“Law enforcement, physical and cybersecurity, fire responders and safety personnel generate vast amounts of data from disparate systems that are stored in multiple, separate databases or management systems,” said Brian Schwab, Founder and Principal Consultant at
S3SDC. “Considered separately, these data sets give only a small – and thus incomplete – view of the security and safety situation that exists on the ground. This took huge amounts of time and effort to develop action plans which only addressed very specific threats in an uncoordinated fashion.”
Predictive analytics systems use
complex algorithms to leverage information from these multiple system components and databases, giving security personnel a more complete picture of the current operating environment.
Advantages of predictive analytics
Several cities are using predictive analytics to speed up the time taken to collect and understand large amounts of data to support decision making. It allows better decisions to be made faster than they were just a few years ago. According to Adlan Hussain, VP of Marketing at
CNL Software, there are three main areas where these predictive capabilities are improving security and policing.
- Optimal use of resources: Positioning emergency responders based on historic incidents locations. At peak load times, such as Friday nights, this reduces response times and allows more to be achieved with fewer people.
- Faster detection of crime: Real-time facial recognition, noise monitoring, surveillance video, and license plate recognition (LPR) aided by predictive analytics can allow authorities to reveal hidden patterns, allowing them to detect crime faster.
- Understand crime hotspots: Predictive analytics can be used to more efficiently and accurately plot the locations of serious crimes. The data can be drawn from a wide range of sources and can help government agencies to detect patterns and identify previously unknown crime hotspots.
Being aware of the hype
Although industry experts generally agree on the benefits of predictive analytics in safe cities, some are quick to warn that the technology is a bit overhyped. According to Giovanni Gaccione, Justice and Public Safety Practice Leader at
Genetec, the notion that police departments or other crime-fighting units can detect and stop crime in a city before it happens is unrealistic. While there have been many advancements in security technology, this level of predictive analytics is still far from actualization.
“That said, some intelligent solutions can enhance these strengths by delivering actionable data and enhancing inter-agency collaboration,” Gaccione said. “This technology gives city agencies a better understanding of their environment, allowing them to shave valuable seconds off response times and determine when, where and how to best deploy their resources. That means, whether it’s securing a big city event or handling an unexpected situation, response teams are empowered throughout the entire mission. The latest advances in analytics technology can provide essential tools for local government, law enforcement, and businesses to use to improve the livability of a city while simultaneously addressing security concerns.”