The hereby section is to provide insight into the project progress towards the above set of project objectives. First of all, the progress towards the high-level objective 1 is marked by the advancements made in the sensor node development domain. Throughout the reporting period, the consortium investigated the sensor hardware, their communication protocol and interfaces in order to come up with a design of the sensor node. This process also required the implementation of several amendments in sensor hardware/software in order to reduce the occurring stability issues. The key achievement made in the period is the release of the 1st prototype of the sensor node. The purpose of this piece of hardware and software is the integration of the data coming from the applied sensors in the EU-SENSE system. The node integrates data from the following sensors: Proengin AP4C (Flame Photometric Detector), AIRSENSE Gas Detection Array – Personal (Ion-mobility spectroscopy and Photoionization technology), AIRSENSE GAS Detection Array – Personal (Ion-mobility spectroscopy and Electrochemical cell technology), and TNO SRD detector (based on Metal Oxide technology). Furthermore, it is essential to touch upon the aspect of situational awareness improvement. In the reporting period, the consortium has designed the situational awareness components including situational awareness tool, hazard prediction tool, and threat source estimation tool. The purpose and functionalities of these tools is described, in more depth, in deliverables D3.1 D3.2 and D3.3.
Regarding the second high-level objective, the progress on novel capabilities of detection is mostly reflected through the definition of the data fusion component, which has been organized into a pipeline of activities including classification, identification, and concentration estimation. Furthermore, there have been also developments in the area of environmental noise learning. It has been defined that in the preparedness phase, anomaly detection will be applied in order to monitor unusual situations. In response phase, however, the system will feature “normality detection”, which relies on the comparison of unaffected reference with other sensors in the response phase. Further developments in these aspects will be achieved in the second part of the project, especially once the data from long-term measurements are available for analysis.
The last high-level objective of the project plans the development of dedicated training components of the system as well as showcasing the system with the involvement of end-users. In this area, the consortium has made progress by defining the design of the training component. It has been agreed that the simulation mode will operate on synthetic data and will have access to a database with historical data, which is beneficial for end-users as they have the opportunity to analyze and learn from past events. The details on training components are available in WP3 deliverables including D3.1 D3.2 D3.3 and D3.5. Demonstration of the system, which is realized under WP8, has been confirmed to be held in Nowy Dwór Mazowiecki (Poland). The spot is a professional training centre of first responders in Poland.