public safety departments worldwide have been implementing next-generation work centers, which combine numerous data sources into a single, coherent image using new technology and data analysis software. This allows public safety officials to evaluate a situation in real-time and make appropriate decisions.
The definition of next-generation job centers is exemplified by Real-Time Crime Centers (RTCC). Public safety departments may use data visualization, analytics, and artificial intelligence tools in RTCCs to gain insights into legacy and real-time data feeds. This skill allows for more accurate and timely decision-making.
A cognitive engine, which are AI applications that can process unstructured data from various sources so users—in this case, public safety departments—can easily extract actionable information, is a crucial enabling technology for this type of research. Law enforcement agencies may use these cognitive engines to cull and evaluate body camera footage, edit rich media, generate transcripts, and more.
In RTCC settings, analysts and investigators can consult 15 to 20 separate data sources to identify potential persons of interest in a case. Cognitive engines comb through all of these sources and compile the data into dashboards and mapping systems, allowing for quicker, more concise data on which to make decisions. Cognitive engines are also useful for law enforcement to improve transparency with the public outside of response operations. Cognitive engines can help authorities disclose information about police encounters with people more easily.
A cognitive engine is an artificial intelligence program that takes in unstructured data, analyzes it, and then generates a structured result. Cognitive engines are used for a variety of purposes. There are engines for language recognition, translation, content detection, summarization, emotion analysis, and more in the field of text analysis, for example. Object detection, license plate recognition, and optical character recognition engines are used for video analysis.
Benefits of Cognitive Engines for Public Safety
The use of cognitive engine technology in RTCCs benefits public safety departments in a variety of ways. One is improved transparency. The faster proof can be processed and correctly redacted, the faster it can be published to the public.Cognitive engines are also force multipliers. They assist in reducing the resources and time needed by staff for evidence analysis. Personnel should concentrate on higher-value jobs instead of time-consuming yet low-value tasks like redaction and transcription