 Pyramid is looking to produce a near real time flood risk assessment demonstrator for Newcastle upon time, which will bring together new data sources as well as existing data sources. And in particular, we're going to use City of Newcastle on its wider time catchment. And we're also going to demonstrate that this potential for other areas. And we're going to use a sort of citizen science and community based approach to actually ensure that the tool we produce reflects their needs and concerns and you can see how that will work in that diagram there. And this will involve creating a flood risk component data sets that will include a whole load of existing data sets from the urban observatory that have been collected around the city as well as some novel data from things like bin trucks, for example, and there's a whole load of information as well that we want to assimilate on things like floating debris from CCTV and things like that. So that will allow us to understand some of the problems with blocking and things like that in real time potentially this all of this data gets assimilated into hydrological and hydrodynamic modeling. And then there'll be a web platform that basically takes all of this modeling and data and produces dynamic flood risk maps in near real time at the moment that the idea would be that you could potentially use this type of system in real time in the future. So hi, I'm Liz Lewis from Newcastle University. And talk about the pyramid project, which is basically building a platform for dynamic hyper resolution flood risk modeling. So with kind of flooding at the minute the kind of risk assessment and tools that we use to assess that are really static and their base kind of just on the topography and infrastructure and buildings around. And in reality, flood risk is quite dynamic so kind of a classic example is the boss castle flooding, where there were a whole load of cars that got swept down the river and blocked a bridge and completely change the outline of the flood and the flood in the castle. And so what we're trying to do is stream all of this kind of additional dynamic information and feed it into a central modeling tool which is a hydrological model linked to a hyper resolution and hydrodynamic model, and which can model debris and open and closed floodgates and things like that, and to really capture the changing and evolving flood risk and in flooding scenarios. And so there are a whole load of different data streams that are going to feed into our central modeling tool. And some of them are going to be kind of using artificial intelligence to extract features to create a kind of detailed local flood scape. So for example we've got kind of sensors and cameras on the back of bin lorries that can create a 3D kind of visualization of the area that will feed into the modeling tools, but also working with citizens and communities to use their local knowledge and citizen science sensors and things like that to also feed in to our modeling tool as well. And as also we're going to be obviously using a lot of kind of the national data sets available and leveraging all of the environment agency kind of rainfall and hydrological data as well. So it's kind of bringing together these existing tools and methodologies for extracting all of this flood relevant data and putting it into one big platform and making sure that we're co-developing this platform with our stakeholders and people who are interested in flood risk to make sure that it's giving them appropriate information.