A new way to keep our most vulnerable communities safe from fire is being developed by universities in Sheffield, in collaboration with frontline firefighters.
The project, called PREMONITION, has just been launched at the University of Sheffield and Sheffield Hallam University, and is being carried out by experts in behavioural risk analysis, intelligent simulations and in the study of social processes.
Sophisticated computer modelling techniques, such as large scale agent-based modelling, will enable firefighters to draw together, for the first time, many different strands of information, including geographical, demographical and behavioural data to build up a picture of an area and predict where fires and other emergencies might occur.
The PREMONITION simulation will enable firefighters identify where the most vulnerable areas are – considering, for example, times of the year or the day when risks are greatest. Some of this information is already available to fire services through online sources, or from local authority records, but due to the vast amount of data it is difficult for humans to make sense of this information and combine it in real-time to support decision-making.
Further layers of detail are also being added to the computational model about the routines and behaviours of people living within particular areas, taken from previous research of residents carried out by South Yorkshire Fire and Rescue Service, to produce even more accurate results.
The primary aim of the PREMONITION intelligent system is to enable fire services to make better decisions about where to allocate resources and improve planning and fire prevention initiatives.
Dr Daniela Romano, in the Department of Computer Science at the University of Sheffield, is leading the project, along with Dr Dermot Breslin, from Sheffield University Management School, Dr Stephen Dobson, in Sheffield Hallam University’s Business Systems Department, and experts from South Yorkshire Fire and Rescue Service (SYFRS)
“We live in increasingly complex social networks, with our behaviours being influenced by many interrelated factors,” explains Dr Romano. “Although fire services already have access to much of this information, there is no tool that can help them grasp all of the different strands and utilise the information in real-time to make decisions. This predictive model will unpack this complexity, and help manage resources and services targeted at the most vulnerable groups in our community”.
The project is funded by SYFRS, through its Stronger Safer Communities Reserve, and is targeted, initially, at communities in Sheffield. If successful, the programme could be made available to fire services across the country.
Dr Stephen Dobson in Sheffield Hallam University’s Business Systems Department, said: “The Stronger Safer Communities Reserve has provided an incredible opportunity for university collaboration in its funding of this project. It is great to see the University of Sheffield’s Department of Computer Science, its Management School, as well as Sheffield Hallam Business School, coming together to use research to support the safety and wellbeing of people in the region.”
South Yorkshire Fire & Rescue’s Nicola Smith, said: “The research we are supporting with our academic partners is a cutting edge exploration of behaviours during our prevention and response activities. Partnerships with well respected organisations like the University of Sheffield and Sheffield Hallam University will place us at the forefront of modern approaches to delivering improved community safety.”
