Changes for page f. Test CFT3: Two Detailed Use Cases

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1		-f. Test CFT3: Two Detailed Use Cases
	1	+b. Test: CFT1: Sensor data visualization

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3	3	//<include a short summary of the claims to be tested, i.e., the effects of the functions in a specfic use case>//
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5		-This study evaluates the operational impact and user acceptance of two technological interventions in emergency response: (1) autonomous indoor drones for victim detection and (2) physiological and environmental sensor systems for monitoring first responder health. The primary claims tested are whether these technologies can enhance situational awareness, improve safety, and integrate seamlessly into existing workflows without overburdening personnel. The analysis focuses on stakeholder feedback from first responders, drone operators, and medics, emphasizing usability, trust, and coordination in high-stress environments.
	5	+The goal of this test was to understand what type of information would support each role at different levels (strategic, tactical, operational) in performing their tasks, particularly in decision-making. We focused mainly on the tactical and operational levels.
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7	7	= 2. Method =
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	9	+For each technology, a separate questionnaire was prepared. In total, five distinct questionnaires were created in Survalyzer. All the questionnaires included the same types of questions:
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	11	+1. **General Open Questions**: Firstly, the participants were asked how they thought data could be helpful and how it should be visualized to be useful.
	12	+1. **Information Needs**: Next, the questions focused on the different information needs of tactical and operational roles, asking participants which data they would want and need for their roles.
	13	+1. **Visualization Examples**: Lastly, various examples of data visualizations were shown to get an indication of which role would want to see what type of data visualization. The examples included basic traffic lights, raw data, aggregated data, predictions, and advice. See appendix B for all the designs that have been made.
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10	10	== 2.1 Participants ==
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12		-Three evaluation sessions were conducted. The first session focused on Use Case 2 (physiological and environmental sensors) and included 10 participants, including: firefighters, USAR personnel, and team leaders. The second and third sessions addressed Use Case 1 (autonomous indoor drones). The second session involved 6 participants, primarily general first responders, while the third session included 2 experienced drone pilots who provided technical and operational insights into drone deployment and navigation.
	17	+A total of 12 partners completed questionnaires during the field test in Athens. The health questionnaire was filled out by 5 partners, the communication questionnaire by 2 partners, and the location questionnaire by 4 participants. Although a questionnaire for the gas sensors (also by WEARIN’) was prepared, we decided not to focus on it in Athens since the gas sensor was not used during the exercises. The questionnaires were completed by individuals in various roles, including researchers, drone pilots, paramedics, incident commanders, chief SAR, and firefighters.
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14	14	== 2.2 Experimental design ==
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16		-Each use case was presented through a structured action sequence, simulating realistic operational steps. For every step in the sequence, participants were asked targeted questions using polls. Each sequence included between 2 to 5 questions, designed to elicit feedback on usability, trust, and integration of the proposed technologies. After each participant submitted their poll response, the aggregated results were displayed on screen, prompting open discussion. While not every question led to extended dialogue, many sparked valuable exchanges that clarified user expectations and concerns. At the end of each session, participants were asked two closing questions: (1) their overall impression of the use case, and (2) their expectations for how such technologies might evolve over the next 10 years. These questions helped contextualize the feedback within both current and future operational realities.
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18	18	== 2.3 Tasks ==
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20		-Participants evaluated the deployment, operation, and integration of the drone and sensor systems in simulated mission phases. Tasks included assessing drone startup, autonomous navigation, victim detection, and the use of health monitoring dashboards during live operations.
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22	22	== 2.4 Measures ==
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24		-Feedback was captured through qualitative observations, direct quotes, and Likert-scale agreement ratings on key usability and trust dimensions. Measures focused on perceived usefulness, cognitive load, trust in automation, and integration with team workflows.
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26	26	== 2.5 Procedure ==
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28		-Each session began with a scenario briefing and a walkthrough of the proposed technology in action. Participants were guided through a detailed action sequence representing a typical mission phase. At each step, they responded to poll questions, which were then visualized and discussed in real time. This format allowed for both quantitative and qualitative feedback. The sessions concluded with reflective questions about the overall use case and long-term expectations, encouraging participants to think beyond the immediate implementation and consider future developments.
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30	30	== 2.6 Material ==
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32		-Materials included scenario descriptions, interface mockups (e.g., traffic-light health dashboards), and conceptual visualisations Use case flows. They were shown in the program Mentimeter, to create an interactive session. These were used to prompt discussion and elicit targeted feedback on system behavior and user interaction.
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34	34	= 3. Results =
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36		-Across the three sessions, participants expressed strong interest in the potential of both technologies, while also identifying critical usability and integration challenges.
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38		-In the **first session** (Use Case 2), participants emphasized the importance of minimal setup time, discreet personal alerts, and role-based interfaces. Firefighters preferred default configurations and automation, while USAR personnel were more open to detailed monitoring. The traffic-light status concept and a two-stage escalation model for critical alerts were well received, balancing the need for timely warnings with human oversight. Participants also supported the idea of a dedicated tech or medic role to manage sensor readiness and monitoring.
	37	+= 4. Discussion =
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40		-In the **second and third sessions** (Use Case 1), feedback centered on the need for rapid drone deployment, minimal interference with human responders, and reliable victim detection. First responders highlighted the importance of parallel deployment protocols and geofencing to avoid human-drone conflicts. Drone pilots emphasized the value of having dedicated operators and analysts, and supported the integration of friend-or-foe identification to improve AI recognition. Trust in the system was closely tied to familiarity with the operator and the ability to override autonomy when needed.
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42		-= 4. Discussion =
	40	+= 5. Conclusions =
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44		-The feedback underscores a central theme: technology must adapt to the tempo and structure of emergency response, not the other way around. Both systems were seen as valuable additions, but only if they respect the cognitive and operational constraints of their users. For drones, this means fast, autonomous reconnaissance that complements rather than delays human action. For sensors, it means providing actionable insights without overwhelming users or requiring excessive configuration.
	42	+**Health data**
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46		-Trust emerged as a critical factor in both cases. For drones, trust was built through consistent team assignments and the ability to intervene in autonomous behavior. For sensors, trust depended on discreet, accurate alerts and the assurance that human judgment remained central. The feedback also highlighted the importance of role clarity—who monitors what, when, and how—and the need for flexible system configurations to match different team structures and national protocols.
	44	+Types of health data: heart rate, respiratory rate, body temperature, blood pressure, and mental health were frequently mentioned as essential.
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48		-= 5. Conclusions =
	46	+Reasoning given for roles
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50		-Stakeholders view autonomous drones and health sensor systems as promising tools to enhance safety, speed, and situational awareness in emergency response. However, their success hinges on thoughtful integration into existing workflows, minimal disruption to frontline operations, and clear human oversight. Design priorities should include rapid deployment, intuitive interfaces, role-based alerting, and mechanisms that reinforce trust and coordination. By aligning system behavior with user expectations and operational realities, these technologies can become trusted assets in high-stakes environments.
	48	+* Team Lead - Important for monitoring the overall safety of teams.
	49	+* Medical Personnel - Essential for making critical decisions.
	50	+* Paramedic (Operational) - Necessary for directly treating team members.
	51	+* First Responder - Relevant for personal health and well-being.
	52	+
	53	+Conclusion: Health data is essential for a wide range of roles, but the requirements vary greatly. Medical personnel and paramedics request detailed and contextual data, while team leaders and first responders value summaries and simple alerts more. Transparency in predictive models is necessary to build trust.
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	55	+
	56	+**Location data**
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	58	+Types of Location data: Location data such as GPS coordinates, building heights, and paths to victims were frequently mentioned.
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	60	+Reasoning given for roles
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	62	+* Team Lead - Essential for team coordination.
	63	+* Squad leader (Operational) - Necessary for instructing team members.
	64	+* First Responder - Helps with orientation and finding victims.
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	66	+Conclusion: Location data plays a crucial role in both tactical and operational decisions. Tactical team leaders want aggregated and sector-based data, while operational roles such as squad leaders and first responders need detailed and real-time information. 3D maps and interactive elements are valuable tools to improve navigation and coordination.
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	68	+
	69	+**Communication data**
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	71	+Types of communication data: Respondents emphasized the importance of RSSI (signal strength), signal speed, and interference detection.
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	73	+Reasoning given for roles
	74	+
	75	+* Team Lead - Important for monitoring team connectivity.
	76	+* IT Specialist - Crucial for troubleshooting.
	77	+* Squad leader (Operational) - Relevant for field communication.
	78	+* First Responder - Only needed for personal connectivity.
	79	+
	80	+Conclusion: Communication plays a central role at all levels of USAR operations. Tactical users need extensive analyses to monitor team status, while operational roles such as IT specialists focus on technical troubleshooting. Advisory functions and visual simplicity could contribute to effectiveness in the field.