AI and big data analytics are having a positive impact on almost every sector of human activity, even when it comes to saving human lives. Pioneering emergency responders can now be equipped with a whole set of platforms and solutions that can help them predict, plan for, and react to emergencies and natural disasters more efficiently. As such, this mixture of big data, analytics and are reshaping the science of emergencies.
Prediction and preparation
Computers have been used for weather forecasting since the 1950s, and today some of the world’s most powerful supercomputers are dedicated to climate modelling and meteorology. Decades of research, combined with real-time data including satellite monitoring, and advanced analytical models, including AI, mean that we now have a good understanding of even highly complicated weather patterns and can predict weather events with a high level of accuracy. For governments and emergency services, accurate forecasting means more time to issue warnings to the public, more time to evacuate and more time to prepare response teams.
AI-driven analysis is also bringing much greater insight and understanding into other complex natural events like forest fires, floods or earthquakes. Researchers at the University of Texas at Austin say they have developed an AI algorithm that can predict an earthquake up to a week before it happens. By combining historical data with real-time monitoring, the algorithm has predicted earthquakes with 70 per cent accuracy.
Forest fires are highly complex systems, with many different factors affecting how severe they can become and dictating how firefighters react. Scientists are studying areas in which AI can support fire-control efforts, including research into susceptibility to fires, how fires spread and early detection. A successful pilot project, FireAId, was deployed in Turkey in 2022, and significantly helped firefighters reduce response time and risk.
AI-driven analysis is also bringing much greater insight and understanding into other complex natural events like forest fires, floods or earthquakes.
Presight’s partner NEC has a well-established flood simulation system, which leverages a wide combination of data sources including observed and predicted rainfall, topographical data and watercourse data to give early warning of flooding, predict the areas at greatest risk of flooding, model maximum flood levels, and other flood-related information.
Analytics enables effective emergency response
Prediction and early warning is only one aspect of emergency response, however, and while accidents are inevitable, advanced analytics and AI are increasingly equipping first responders and government agencies with unique tools to manage incidents and save lives.
Like any digital transformation, there are many different technologies that come together to improve the capabilities of emergency services. Take the example of a fire in an industrial area. When the initial reports come in, data sharing through mobile devices, geolocation services and citizen apps can begin to build a picture of the accident scene. Traffic cameras can share data in real time, and route planning and analytics applications can share the fastest route to the incident with emergency crews, as well as automatically assign the right sort of response teams to tackle the situation.
On the scene, response teams can access data from different sources, including imagery from drones and body cameras, and share that data with controllers at the command centre so that they can map the incident, formulate the best response plan and collaborate with other agencies as required. Medics can access patient’s medical records on the spot via mobile devices and connect in real time to medical experts and assign them to facilities that have the right specialisms and capabilities to treat them. The same traffic route analysis can also be used to plan the best route for ambulances.
By integrating emergency responses with municipal data and mapping, systems can also automatically analyse the surrounding area and raise an alert to any potential secondary hazards, like a nearby chemical warehouse that might be in danger from the primary fire. Automated emergency alerts, traffic diversions and specific evacuation instructions can be broadcast to the public via apps.
With advanced analytics support, many of the connections and responses required for emergency response can be calculated automatically or according to pre-set response plans, greatly cutting the time to action. By combining all these different sources of data and connecting different stakeholders and teams, analytics solutions can deliver an unprecedented level of insight, planning, response and follow-up and revolutionise emergency responses and save lives.
– The writer is the Chief Operating Officer of Presight
