On September 29th, 2021 a field testing activity for the INGENIOUS project took place at HRTA’s training facilities in Afidnes (ATC), Attica region of Greece. The INGENIOUS project is about ensuring a high level of protection and augmented operational capacity for First Responders (FR) working inside the disaster area.

The main objectives of these two Small Scale Field Tests, SST#7 and SST#8, included the integration of the specific components of the INGENIOUS Toolkit in real-life conditions, in order to provide testing, assessment, validation and improvements for further development steps. FRs have a significant role as they are the end-users that in future will depend on technologies like these. Hence, robustness, accuracy and reliability of the components are crucial acceptance factors.

From the Technical partners of the consortium, EXUS and CERTH are the developers of Fusion Engine (FE) & Expert Reasoning Engine (ERE), Worksite Operations App (WOA) (EXUS) and Social Media App (CERTH), while from FRs’ side HRTA and ERTZ were present. The tested components of the INGENIOUS Toolkit for Collaborative Response were presented by the Technical partners and FRs interacted during the event with a mixed team from Greece and Spain.  

The impression FRs gained is that the overall development of these technologies is on track, although it needs further development and some minor changes in order to be operationally usable. Based on the FR comments, the Fusion Engine & Expert Reasoning, as well as the Social Media App can be included in the standard FR tools in the field, helping in gathering information and enhancing the situational awareness, as well as protecting them from unseen hazards.   

Test 1 – Fusion Engine

The components that were demonstrated/tested during SST#7 included the Fusion Engine (FE), the Expert Reasoning Engine (ERE) and the Worksite Operations App (WOA). The use case that was used involved first response in a single site after a terror attack in public space, as it was defined at previous stages of the project.

The Fusion Engine was tested with incoming data received by the present components (either physically present or remote) and by data generators to replicate the input from components where data were not yet available. Several scenarios and conditions were tested. Functionalities that were tested included: Interoperability with components, registration of resources, FR Health Status early warning, Danger Zone Rating, among others.

Test 2 – Expert Reasoning Engine

The Expert Reasoning Engine (ERE) was tested in terms of health status warnings and the detection of abnormalities and communication with the Common Operational Picture Platform (COP) through alerts that feature the status the severity or the urgency of an incident. Within the scenario, there was a need to monitor the health status of the First Responders. To tackle this, the Expert Reasoning component receives the measurements of the vitals and processes them for detecting abnormalizes. These abnormalities in the measurements can be the results of dehydration, exhaustion and heatstroke. As a result, the component pushes the corresponding alerts to the COP to monitor the health status of the First Responder.

In this stage, the knowledge base of the module was implemented regarding the FR’s status. Each person contains entities (Figure 1) that are possible to be impacted by the crisis. The result of the impact is visible (Figure 2) through the vital signs (body temperature, blood oxygen level, heart rate, etc.) that are measured by the other modules, and lead to the physiological condition (Tiredness, asymmetric waking etc.)

FR status. Result of the impact

Test 3 – Worksite Operations App

The Worksite Operations App (WOA) demonstrated functionalities regarding the resource management, decision support and system integration with FE and other online resources.

Technological challenges

The functionalities demonstrated for these three components (FE, ERE and WOA) satisfied the technical requirements that were established by the technical partners and end users, such as location information of victims, FRs, and incidents, allow FRs to select areas and display information, raise alarms regarding the physical state of FRs among others.

Next steps for further development 

SST#7 was the first opportunity for Small Scale Field Test of the FE, ERE and WOA components. Although current setbacks e.g. COVID-19 and fires affecting the HRTA location, the STT was conducted successfully and with overall positive feedback from the end users. Further information collected through the formal evaluation but also through the experience of field deployment led to additional improvements of the components. Specifically, the next steps will include:

  • provide to COP info on hover of rated zones (type of gas, concentration)
  • WOA to show points of interest in map (such as camp, fuel station, etc.)
  • Continuous integration with other components of the Ingenious system

Also, special attention will be given to improving the security of the developed solutions and focusing on the collection and application of real time data.


Test 4 – Social Media App

During the wildfires, people in the affected region used to post on social media to learn and inform about critical information about the fires. In addition, FR teams can use this information to their advantage. As a result, the Social Media App aims to collect the related information and filter out the irrelevant in real-time by detecting events related to a simulated large forest fire near residential areas.

During the SST#8, real tweets were posted, in real-time, on the Twitter platform. As Twitter is a public platform, those tweets were encoded with particular hashtags and codes to avoid false alerts to the platform’s users (Figure 3). The new upcoming tweets are stored and processed near-real time by the appropriate services. Then, the event detection method collected and grouped the relevant tweets based on the time posted and the location. In particular, each group of tweets refers to an event detection message. The corresponding events with the post analysis information were sent from FE to COP in order to be monitored in the COP platform (Figure 3).

SMA-COP integration – Screenshot of the live demonstration
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