The role of assistive AI in a real-time crime center

Real-time crime center (RTCC) is a term that is seen more and more in the public safety industry. RTCCs are essentially centralized technology hubs used by law enforcement agencies to track data in real time, identify patterns and to prevent and reduce crime. According to the United States Department of Justice (DOJ) Bureau of Justice Assistance (BJA), the mission of an RTCC is “to provide a law enforcement agency with the ability to capitalize on a wide and expanding range of technologies for efficient and effective policing.” Many major cities have established RTCCs in order to better protect their residents, officers and communities.

RTCCs can house members of one or multiple agencies and receive large amounts of data from many sources across their jurisdictions, including video cameras, sensors, license plate readers (LPR), gunshot detection, drones, facial recognition, computer-aided dispatch (CAD) systems, records management systems (RMS), electronic monitoring, the National Crime Information Center (NCIC) and more. This influx of data gives the RTCC a “bird’s eye view” of a situation, but it also makes zeroing in on actionable data to pass to public safety answering points (PSAPs) or emergency communication centers (ECCs) tedious.

That’s where real-time incident center as a service technology with assistive AI makes all the difference.

Identifying actionable data with assistive AI

RTCCs receive copious amounts of data from many different systems, but not all data is relevant to every situation, and while an RTCC may create a common operational picture (COP), data overload can lead to an inability to act quickly and with the right information. What’s more, some RTCC systems are homegrown, meaning they are customized or built by the agencies themselves and may not function as seamlessly as they should and lead to higher cost of ownership.

Commercial-off-the-shelf (COTS) real-time incident center as a service technology with embedded, assistive AI can not only integrate data from disparate systems and allow for collaboration between users and agencies, but also sort through data in real time to provide actionable information quickly, as a situation is unfolding.

This technology puts the “real-time” in real-time intelligence. As data floods into the RTCC, assistive AI is simultaneously working its way through the information, flagging anomalies, patterns, similarities and trends and enabling proactive decision-making in real time. This intelligence can be disseminated to first responders or other teams in the field.

Considering a scenario

Here’s an example of how this technology can be used in the real world.

An RTCC crime analyst uses real-time incident center as a service technology with embedded assistive AI to monitor incidents from local police agencies. Since crime does not stop at an agency’s border, technology provides controlled access to data from neighboring agencies using secure data-sharing rules. The analyst uses the data to identify emerging trends, location hotspots and other patterns. At the same time, the AI component is running simultaneously in the background using advanced statistics, ML and AI to assist the analyst. The assistive AI detects a statistical anomaly and sends a notification to the crime analyst. In the last two days, five car thefts have occurred in the North Shore district and neighboring jurisdiction. The analyst creates a smart shape to identify incidents and IoT devices in nearby locations, then turns on an open GIS layer to see the field of view of the cameras, helping her locate which camera is most useful. The crime analyst reviews all the incidents within the shape by the AI component’s natural language processing capabilities. It highlights the names, locations and addresses associated with each of the incidents. She recognizes an alias used by a local gang and provides this information to the detectives in charge.

That’s just one scenario in which real-time incident center as a service technology with embedded assistive AI can help RTCCs sift through data quickly, get information to those who need it and reduce criminal activity.

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Learn more about HxGN Connect, Hexagon’s real-time incident center as a service with embedded assistive AI.

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