Domain Awareness was initially developed by U.S. law enforcement to enhance urban public safety. However, real-time awareness and decisions-making applications extend across the physical and digital spectrums of the public safety, law enforcement, intelligence, military, space, cybersecurity, maritime, and environmental protection domains. Emerging Internet of Things (IoT) sensor technologies, 5G network telecommunications, and Artificial Intelligence (AI) empowered Machine Learning means that we will increasingly be able to automatically “sense” and then make informed human decisions about what is taking place around us, across both structured (urban) or unstructured (rural) spaces.

 

Incident detection, object tracking, pattern recognition, and identity management are only a few of the applications of Domain Awareness technologies, yet they enable limited resources to effectively manage increasingly large and complex environments. These technologies have already empowered organizational efforts to identify watch-listed persons and suspicious packages, manage facility security and access, and identify and prevent illegal poaching. However, these technologies could also enable individuals and organizations to collaborate across disparate boundaries or in social space to identify and correlate: drug smugglers and distributors with drug overdoses; human traffickers and prostitution with missing persons and suspect persons at risk; and suspicious activities with individual personal security.

The New York City Police Department (NYPD) is the largest state or local police force in the U.S., charged with providing public safety and security. Since 1993, the NYPD supported a 75% decrease in crime. NYPD achieved this success through changes in policy, tactics, use of analytics, and operations research. These changes are leveraged through the NYPD's Domain Awareness System (DAS). The NYPD DAS is a citywide network of sensors, databases, devices, software, and infrastructure that informs decision-making by delivering analytics and tailored information to officers’ smartphones and precinct desktops.  

Development of the DAS began in earnest in 2008; since then, the NYPD uses the DAS to employ a unique combination of analytics and information technology, including pattern recognition, machine learning, and data visualization. By improving the efficiency of the NYPD’s staff, the DAS saved an estimated $50 million per year. Most importantly, the NYPD uses the DAS to combat terrorism and improve crime-fighting effectiveness.