Designed to predict and mitigate risks across a range of industries, our incident modelling solutions provide actionable intelligence to stakeholders looking for greater situational awareness and preparedness in the face of emerging threats and hazards. 

Fuelled by a range of data sources and individual models, our platforms were created with the goal of better understanding high-risk scenarios such as oil spills and cyber attacks. As a result, users can more effectively and efficiently orchestrate a response – saving time and minimising associated risks in the process.  

To achieve this, each of our models explores and examines hundreds of variables, as well as underlying probabilities, developed from a core understanding of the physics and other sciences involved. 

With these tools in place, our models can predict possible future outcomes based on previous trends, helping users to gain a better understanding of risks and explore a range of possible outcomes.  

Incident modelling, agility, and fresh perspectives 

Our incident modelling capabilities are enabled through the combined passion, experience, and expertise of our specialist team.  

Backed by specialisms in science and software, we hope to provide users with a unique perspective on a range of challenging environments, from explosive threats in urban environments to satellite disruption and damage.  

With this viewpoint enabled, our users can rapidly respond to the latest threat, armed with agility and the most effective and actionable intelligence available. 

How do we create our simulations? 

Creating a new simulation primarily involves five main stages. We begin by understanding what output information the user needs, before developing prototypes, undergoing verification processes, and ultimately ensuring the system is user ready and secure. In detail, these steps are: 

Understand what output information the user needs and what information is available 

Our solutions can’t progress without this stage, and it provides the foundations needed to build intelligent solutions for our users.  In this stage, we strive to understand the user requirements, allowing us to identify the data sources needed to model and simulate potential risks effectively. 

Research the problem and review samples of the input data we expect to be available 

Once we understand the user requirements and have identified what information is available, we can begin the second phase of our research. This involves researching the specific risk or incident that we will be modelling in more detail and exploring what input data is currently available. Our models need data to fuel them, so reviewing samples of input data to assess their quality and fidelity is crucial.  

Develop model prototypes 

Developing model prototypes begins with a simple prototype of the model, which we evaluate and assess. Once the first model prototypes have been evaluated, we continue to produce more iterations until our models are fully capable. We’ll then develop an integration-ready prototype, performing a trial integration into the host application.  

Perform verification and validation 

With our model prototypes complete, we can then move into the verification and validation phase. Verifying our models involves testing that they are performing in line with our software specifications. Validation, on the other hand, involves confirming that our models provide the necessary answers or predictions that match with real world or lab and field data. 

Recently, we verified the accuracy of the MarineAware platform in a joint investigation with the STFC, in which our models were assessed in their oil spill predictions of a known case that occurred off the coast of Corsica in 2018. To learn more about this verification process, and what metrics were used, read our blog here.  

Productionise the system 

Productionising the modelling system is often the last phase of the development cycle, excluding regular evaluations and maintenance.  

As well as confirming that the model is user ready and fully responsive, this step also involves ensuring that the software is fully tested, and fully secure (achieved through performing a cyber security review). As a result, we can supply our users with the actionable intelligence needed for greater situational awareness, without compromising on reliability or security.  

Our incident modelling tools in the real world 

Our incident modelling platforms have been deployed and built for a wide range of recognised use cases, including helping users:  

• Model how hazardous chemicals are released and dispersed in dense urban environments, as well as their effect on people – including those inside a building. 
• Explore the trajectory of a sophisticated cyber attack, as well as its intended effect 
• Predict the effect of an oil release from a ship on coasts 
• Examine the movement of crowds in several environments such as stadiums and town centres
• Simulate the effect of satellite outages 
• Integrate various models into training simulations (Under the SERAPIS SSE programme) 

Committed to ensuring preparedness 

Backed by a team of dedicated specialists and team members, our incident modelling platforms empower users through many environments with the actionable intelligence needed to make informed, strategic decisions that may mitigate risks and streamline operations.  

Learn more about our range of incident modelling solutions here.