How Emergency Response is Evolving with Next-Generation 911

When 9-1-1 was first introduced, it was built to support landlines and analog devices. With 80 percent or more of 9-1-1 calls now coming from wireless devices, Next-Generation 911 (NG911) was created to reflect the mobile, digital, fast-paced world we live in and to support a range of communication mediums including texts, photos and videos. This means that a citizen can report a crime no matter where they are, and provide a fuller picture for first responders to evaluate a scene. Emergency workers are then able to respond with the appropriate resources needed for each scenario and deal with it more effectively. As a tool built for the modern world, NG911 will evolve emergency response as a result. 

Before NG911, a 9-1-1 call only included a written description of a scene provided the caller, which was then passed on to emergency responders. As these calls are often made under severe distress, the details of the scene may be warped or not provide an accurate depiction of the situation. Using what little information they had, and from a potentially unreliable source, workers needed to determine how to approach a situation. Now with NG911 video footage and photos help paint a larger picture, which can improve situational awareness and response effectiveness.

With greater access to information provided by NG911, data sets around 9-1-1 calls are growing. While this is helping response workflows and processes become more accurate and efficient, artificial intelligence (AI) is needed to help parcel details into one cohesive idea. Information that was once manageable by a single human is becoming too complex to handle. Therefore, AI will be critical in ensuring that data can be analyzed rapidly, prioritized, and presented in a way that makes the most sense to officers. Other emerging technologies, including machine learning (ML), automation and the Internet of Things (IoT) are also essential in making sure that information is available on scene, and relayed in a concise manner.

Before, officers had to rely on their past experience to react to a present situation, now they can use data to determine the best possible solution. According to a study by PwC on policing in the networked world, police forces can leverage data to help shift policing to a more proactive model. ML and AI do just that. They can sort and categorize information to reveal trends and ultimately forecast a response with the highest success rate. These tools are supporting the goal of NG911, by allowing real-time information from the field to flow seamlessly to the 911 network and help first responders be more productive.

Though there’s a clear argument to be made for the implementation of NG911 and the emerging technology to support it, it has yet to be adopted on a national level. According to the FCC’s Thirteenth Annual Report to Congress on 911 Fees, forty-three states, the District of Columbia, and Puerto Rico reported engaging in NG911 programs in calendar year 2020. NG911 requires new computer hardware and software, which prevents agencies with smaller budgets from using it, while others would just prefer to stick with their current system. But as NG911 grows nationwide, emergency response will evolve as a result and agencies using old technology will be left behind. 

Just as NG911 was developed for a modern, digital world, emergency response is required to be more mobile and flexible than ever. Mobile devices like the TOUGHBOOK G2 that feature 4G LTE and 5G connectivity are imperative to performing critical duties and staying connected anywhere, for seamless communication between vehicles. The availability of data is also only as useful as the ability to access it, making connectivity even more important. With the speed of information, citizens have higher expectations for public safety officers and their response. NG911 combined with technologies such as connected mobile devices, ML, AI and IoT will help improve situational awareness for all parties involved, and live up to these expectations.