Last week EXUS AI Labs demonstrated successfully components, such as the mutli-source information fusion engine, expert reasoning system and data exploitation and application for enhancing operational capacity, that it has been developing for the INGENIOUS project. The Multi-Source Information Fusion Engine was tested for near real-time data processing and quality of data (across different dimensions), its ability to produce alerts from heterogeneous sensors (e.g., boots) and raise alarms for First Responders (FRs) in danger, communication to and from First Responders and attributes related to scalability and post processing capabilities. The components where demonstrated across a number of use cases.
One of the intelligence services that was shown for the first time was the Map zone classification based on data from available sensors. Zones across the worksite are rated, based on readings from sensors and their classification (in terms of danger for the FRs) is visualised through different colouring of the zones in the map. The system took as input the coordinates for each FR carrying the sensors at any given time, the temperature reading from the boots and the gas sensor reading. Danger gas zones were depicted as red/orange/yellow according to severity. A clustering algorithm was used to create affected areas based on neighbouring sensors.
Feedback was collected from end users and the different components were evaluated and validated across the set of requirements. Further improvements were discussed with the need for field tests being identified.