Artificial Intelligence (AI), and specifically Machine Learning (ML), are being tested in an increasing number of fields, including data-centric environments. Image or text analysis, speech recognition, chatbot interactions, custom machine learning models… all these are elements that can directly benefit public safety and security organisations.
But can Artificial Intelligence help save more lives? We believe that AI has the potential to enable significant savings compared to current methods employed by the emergency medical services sector, as well as offer added benefits of automated analytics to measure dispatch quality and continuous training of human operators.
ai Special Project
In 2024, EENA launched a Special Project on AI for PSAPs and emergency dispatch centres, focusing on testing various AI applications in PSAPs and control rooms across Europe.
ai & emergency services
In an emergency, every second counts. PSAPs (Public Safety Answering Points) are high pressure environments, where multiple streams of data – location, caller audio, and other contextual data – can interact and appear simultaneously. For the most efficient outcome, it is essential to use and understand all of these resources. Machines can process these huge amounts of data faster than humans can, and also learn how to constantly improve.
How can Artificial Intelligence benefit the work of emergency services?
- Artificial Intelligence can process multiple streams of data almost instantly, ensuring that nothing is missed by a human call-taker that may be essential to the emergency response given.
- AI can be used to enhance the audio quality of calls to emergency services, providing services such as automated captions or translation. This saves call-takers time by not having to ask the caller to repeat themselves, for example.
- AI can be used to design, and implement, call-takers’ decision trees – allowing for faster and more efficient dispatch decisions.
- AI can plan the routes of emergency vehicles. For example, AI can give emergency departments an estimated time of arrival for an ambulance, giving hospitals vital time to prepare for patients.
- AI can monitor social media for faster indications of potential disasters before emergency services may be made aware through emergency communications.
- Social media listening can identify when a new topic is trending, alerting authorities and first responders to respond in a timely manner.
- During a large-scale event, there may be longer wait times when trying to reach emergency services – due to a limited number of humans able to man the physical lines, which may be receiving thousands of calls. A chatbot, a computer program designed to simulate conversation with users, can respond to multiple queries simultaneously: freeing up human call-takers for more complex inquiries.
- AI and ML can assist in cybersecurity and monitoring cyberspace, such as fraud detection and helping to find information on the various layers of the web.
- With the broad expansion of IoT devices and the opportunity to integrate those sensors into the PSAP; better sensor integration, coupled with edge analytics, can increase the visibility and understanding (situational awareness) on what is occurring.
eena ai project with Corti: 2018
EENA launched a year-long joint initiative with Corti in May 2018 to pilot AI support aimed at improving emergency medical service operations. The initiative was implemented in two European countries and provided real-time decision support for emergency dispatchers responding to cardiac arrests, enhancing human decision-making with AI.
How did it work? A real-time automatic speech recognition technology provided recommendations and guidance to medical dispatchers handling emergency calls. During each call, the data was analysed and compared with historical data from millions of previous emergency calls, enabling the platform to learn over time. As understanding of the incident evolved throughout the call—based on both analysed data and caller input—Corti learned to predict the criticality of the situation, delivering real-time alerts and recommendations to the dispatcher.
EU Legislation
The European Commission has proposed the first EU regulatory framework for AI. It says that AI systems that can be used in different applications should be analysed and classified according to the ‘risk’ they pose to users. The different risk levels will mean different levels of regulation: once approved, these will be the world’s first rules on AI. The European Parliament adopted its position on the AI rulebook with an overwhelming majority on 14 June 2023, paving the way for the interinstitutional negotiations set to finalise the world’s first comprehensive law on Artificial Intelligence.
Find out more about the EU AI rulebook in our webinar: ‘The EU AI Rulebook and What It Could Mean for Public Safety’.
