# Speaking of Safety: Drone-Based Voice Communication for Industry

Chandhawat Boonyard, Stine S Johansen, Christophe Jouffrais, Anke M Brock, Timothy Merritt

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Chandhawat Boonyard, Stine S Johansen, Christophe Jouffrais, Anke M Brock, Timothy Merritt. Speaking of Safety: Drone-Based Voice Communication for Industry. Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction, Mar 2026, Edinburgh, Scotland, United Kingdom. 10.1145/3757279.3785563. hal-05457600

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# Speaking of Safety:
## Drone-Based Voice Communication for Industry

Chandhawat Boonyard

chandhawat.boonyard-ext@enac.fr
Fédération ENAC ISAE-SUPAERO
ONERA, Université de Toulouse
Toulouse France

Stine S. Johansen

stinesl@cs.aau.dk
Aalborg University
Aalborg Denmark

Christophe Jouffrais

christophe.jouffrais@cnrs.fr
CNRS, IPAL
Singapore SG

Anke M. Brock

anke.brock@enac.fr
Fédération ENAC ISAE-SUPAERO
ONERA, Université de Toulouse
Toulouse France

Timothy Merritt

merritt@cs.aau.dk
Aalborg University
Aalborg Denmark

<figure><img src="image_2.png" /><figcaption>**Figure 1:** A conceptual illustration of our voice-based drone system acting as an on-site safety agent. Left: Human operators in the control room deploy the drone. Right: The drone autonomously delivers a message to a worker. The system is designed to bridge communication gaps by adopting a multi-modal approach that integrates sound, structured voice advisories, and physical presence to establish authority and ensure compliance in high-risk industrial environments.</figcaption></figure>

## Abstract

Ensuring the safety of personnel at large industrial sites is a significant challenge. Misunderstandings and increased safety risks are related to communication, as traditional non-targeted alerts like sirens are often ineffective. To address this, we propose a drone-based system that uses voice interaction to deliver timely and targeted safety advisories. This paper presents a multi-stage, user-centered study, beginning with formative interviews with security and safety managers and culminating in an on-site evaluative study with personnel at two biomass power plants. Through our study, we identify

key design insights for creating a drone that is perceived as an official, authoritative, and non-threatening entity. We provide design guidance for using sound and movement to signal intent, creating a voice persona that balances authority with clarity, and designing interaction flows to manage confusion and non-compliance. The results demonstrate the system's potential not only to enhance safety compliance, but also to mitigate interpersonal confrontation. First, we provide an empirically-grounded understanding of contextual safety challenges, which informs a set of design principles for intelligible and socially acceptable voice advisories from drones. Second, we present results from an in-situ evaluation of a working prototype that demonstrates its effectiveness in a real-world setting.

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This work is licensed under a Creative Commons Attribution 4.0 International License.
HRI '26, Edinburgh, Scotland, UK

© 2026 Copyright held by the owner/author(s).
ACM ISBN 979-8-4007-2128-1/2026/03
https://doi.org/10.1145/3757279.3785563

## CCS Concepts

* Human-centered computing → User studies; Scenario-based design; Auditory feedback.
## Keywords

human-drone interaction, sound, voice, industrial safety, critical infrastructure

**ACM Reference Format:**

Chandhawat Boonyard, Stine S. Johansen, Christophe Jouffrais, Anke M. Brock, and Timothy Merritt. 2026. Speaking of Safety: Drone-Based Voice Communication for Industry. In *Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction (HRI '26)*, March 16–19, 2026, Edinburgh, Scotland, UK. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3757279.3785563

# 1 Introduction

The resilience and safety of critical infrastructures are of paramount importance, particularly in complex industrial environments like power plants [55]. A significant challenge in current safety protocols is ensuring the well-being of external personnel, such as vendors or outsourced contractors, who may not be fully integrated into the plant's formal communication channels [17, 49, 51]. This communication gap can lead to dangerous misunderstandings and an increased risk of incidents or accidents [41]. Traditional, non-targeted alerts such as general sirens can be ineffective, as personnel may develop "alarm indifference" and fail to respond, assuming it is merely an exercise [17, 49]. Furthermore, standard communication devices like mobile phones or radios are often impractical; heavy personal protective equipment (PPE) makes vibration alerts imperceptible, and hearing protection blocks ringtones. This creates a reliance on sending personnel to physically locate and instruct individuals—a process that is inefficient and time-consuming in large facilities.

In response to consistent safety demands, many industrial sites such as power plants, have begun integrating robots or drones into their operations to improve safety measures [4, 21, 29, 45, 58]. Voice has emerged as a natural channel for human-drone interaction [64, 69], with much of the existing work focusing on using voice commands for direct flight control [42]. While some research also proposes using drones to broadcast safety advisories [6, 48], less is known about the specific design requirements for making these interactions effective in noisy, high-stakes industrial contexts. It remains less clear, for example, how a drone's vocal characteristics, integrated sounds, and physical movements should be designed to effectively convey authority, ensure intelligibility, and gain social acceptance from personnel on the ground.

The core objective of our work is to understand how to design a drone's communicative behaviors—including its voice, sounds, and movements—to deliver safety advisories that are intelligible, authoritative, and socially acceptable to personnel on the ground [16, 63]. This work investigates the design of these interactions in safety-critical scenarios, particularly where drones can act as intermediaries to provide advisories to personnel in communication blind spots or when they engage in unsafe actions [26, 44].

Specifically, this proposal seeks to answer the following research questions for external personnel in hazardous, noisy, industrial settings:

**RQ1:** What are the critical information needs and interaction requirements for voice-based drone advisories?

**RQ2:** How can a drone's vocal characteristics, sound cues, and physical behavior be designed to effectively convey authority and ensure safety compliance?

To answer these questions, we employed a multi-stage, user-centered research methodology designed to first gather contextual insights and then evaluate a designed system in a realistic setting of biomass power plants. This paper presents the following contributions to the field of Human-Drone Interaction: (1) An empirically-grounded understanding of the contextual safety challenges and communication protocols from stakeholder perspectives; (2) A set of actionable design implications centering on a tiered interaction model and the drone's role as a neutral intermediary for creating intelligible, context-aware, and socially acceptable voice advisories from drones; and (3) The results from an in-situ evaluation of a working prototype, assessing its usability, and practical viability "in the wild".

# 2 Related Work

To situate our work, we review literature from three key areas that inform the design of a drone-based voice advisory system. We first discuss the established use of robots and drones in industrial and safety-critical applications, highlighting their primary role as remote sensing platforms. We then elucidate the specific challenges of using voice and auditory displays in Human-Robot Interaction (HRI), focusing on the complexities of designing for noisy, real-world environments. Finally, we examine challenges of trust and authority when an autonomous agent is tasked with providing guidance and instruction to non-expert users.

## 2.1 Drones in Industrial and Safety-Critical Applications

The use of mobile robots to perform inspection and monitoring in hazardous industrial environments is a well-established field of research [45]. For decades, autonomous and teleoperated ground robots have been developed to reduce human exposure to risks in high-radiation zones within nuclear power plants [40] and to automate the inspection of equipment in high-voltage power substations [23, 54]. The primary motivation for these systems is to replace human operators in repetitive or dangerous tasks, thereby saving time, reducing cost, and improving safety [8]. These robots typically function as mobile sensor platforms, carrying instruments like infrared thermographs and cameras to gather data on equipment status, which is then analyzed remotely to detect anomalies such as hot spots or other faults [74].

More recently, the focus has shifted towards using aerial robots, i.e. drones, which offer greater mobility and the ability to access areas that are difficult for ground-based systems [24]. Many studies have looked at how drones can be used for radiation monitoring, particularly in response to nuclear accidents such as the one at the Fukushima Dai-ichi Nuclear Power Plant [61, 62]. Drones equipped with specialized radiation sensors have proven effective for mapping contamination and enhancing situational awareness in areas where human presence is dangerous or impossible [4, 29]. This capability is critical for establishing detailed decontamination plans and supporting emergency response actions.
While this prior work demonstrates the value of robotic systems in industrial settings, it predominantly frames the robot or drone as a remote sensing tool for an expert operator. The information gathered—be it thermal, visual, or radiological—is typically transmitted to a control room for analysis by a human who then directs the subsequent actions. There is significantly less research exploring how drones can interact with and provide real-time, actionable safety guidance to non-expert personnel who are co-located with the drone in hazardous environments.

## 2.2 Voice and Auditory Displays for Human-Robot Interaction

Communication and safety are among the key applications identified in prior human-drone interaction (HDI) research [24]. Voice has emerged as a promising modality for HDI, to enable hands-free control of the aerial vehicle. Prior work investigates the use of speech recognition to transform human speech into commands to control the drone's flight and maneuvers [18, 42, 65, 80]. Such voice-control paradigms have been explored for various applications, including specialized contexts like police operations [26]. While less common, some research has explored the inverse, where a drone uses its own speaker and voice recognition system to initiate contact and detect victims in search-and-rescue scenarios, highlighting the potential for bidirectional vocal interaction [79].

Beyond simple command recognition, vocal characteristics significantly influence trust [71]. Context is crucial; for instance, urgent tones in emergencies have been shown to reduce cognitive load [39]. However, real-world deployment faces acoustic challenges: drones generate distracting “consequential sounds” [3], and their audibility is heavily impacted by movement and background noise [1]. Consequently, vocal advisories must be engineered to ensure intelligibility over this dual layer of industrial and flight noise.

Simply increasing the volume of a drone's voice is not a viable solution, as this can lead to other human factor issues. For example, in a field trial with firefighters, audio instructions from a drone were found to be a primary source of information overload, a critical problem in high-stress situations [44]. While prior work has explored non-alarming auditory cues for situational awareness in autonomous vehicles [20], to our knowledge this has not been explored in HDI.

This indicates a need for modified approaches beyond merely broadcasting commands. A clear gap remains in understanding how to design and structure a drone's *spoken* advisories. The challenge lies in creating messages that are not only intelligible in a noisy environment, but are also appropriately designed in tone and content to convey authority, build trust, and guide action without overwhelming the recipient.

## 2.3 Trust and Authority to Guide and Instruct Non-Expert Users

For an autonomous system to be effective in a safety role, it must be able to successfully guide and instruct people who are not trained operators. However, the success of such instructions depends on the user's willingness to comply, which is deeply rooted in their trust in the system. This is especially critical in time-sensitive situations, where a single performance error by a robot can cause a significant

drop in human trust and negatively impact their decision to follow its lead in subsequent interactions [56]. As autonomous systems become more prevalent, designing them with the ability to build and actively repair this trust is essential for creating effective and acceptable human-machine relationships [15].

Communication design is central to establishing this trust. The way an agent is presented to a user can prime their beliefs about its motives, influencing perceptions of its trustworthiness and empathy [52]. The agent's voice is a particularly powerful tool in this regard (see section 2.2). Even the perceived intelligence demonstrated through a robot's ability to understand natural language, such as indirect speech, can significantly improve user trust and the sense of teamwork [81]. These findings underscore that the linguistic and paralinguistic features of a robot's speech must be carefully designed to match the interaction's context and goals.

While the principles of trust and communication in HRI are well-studied, the specific social dynamics of an *aerial robot* acting as an on-site authority figure are less understood. A drone's unique physical presence creates a distinct interaction context, where factors such as its specific design features [76], proxemic distance, movement, legible motion [67], and inherent noise affect user perception [13, 60, 75]. Importantly, the suitability of a drone's involvement largely relies on the specific context in which it is utilized, with greater acceptance in scenarios perceived as more severe [25]. There is emerging work exploring how drones can be used to enforce social norms, for example, by using gestures to discourage smoking in prohibited areas [38]. However, a clear gap remains in understanding how to design interactions for a drone that must enforce mandatory safety rules in a high-stakes industrial environment. The challenge lies in designing an agent that can establish sufficient authority to ensure compliance, while simultaneously maintaining user trust and mitigating the negative perceptions that can arise from its machine-like nature.

## 2.4 Summary

In summary, while the literature confirms the value of drones as remote sensors in industrial environments and explores voice interaction in HRI, a clear gap remains. Prior work has not adequately addressed the challenge of designing a drone that acts as a direct, on-site *communicative agent* for non-expert personnel. Specifically, there is a need to understand how to design voice advisories that are not only intelligible over environmental and drone's noise but are also socially acceptable and effective at establishing sufficient authority to ensure safety compliance without eroding user trust. This paper directly addresses this gap by presenting the user-centered design and in-situ evaluation of a system created for this purpose, leading to a set of empirically grounded design implications for future systems.

## 3 Methodology

Our research followed a multi-phase, user-centered design process, grounded in the principle of making sense of the lived experience of personnel in their operational environment [78]. This approach progressed from formative needs-finding (Phase 1), through a design and conceptualization stage (Phase 2), to an in-situ evaluative study of a derived system concept (Phase 3). This phased methodology
was chosen to ensure that our final design was not only technologically sound but also deeply rooted in the contextual needs and realities of its intended users.

A total of eight participants were recruited for their professional expertise in critical infrastructure management, safety, security, and drone technology. Participants were drawn from two biomass power plants and one drone technology consultancy. Three management and safety personnel participated in Phase 1, and seven participants (including two from the first phase) in Phase 3. Table 1 provides a summary of the participants’ roles and their involvement in the study.

<table><caption>Table 1: Demographics of the 8 study participants across the two research phases.</caption><thead><tr><th>Participant(s)</th><th>Expertise / Role(s)</th></tr></thead><tbody><tr><td colspan="2"><strong>Phase 1: Formative Study (n=3)</strong></td></tr><tr><td>P1</td><td>Management personnel from Site B</td></tr><tr><td>P2</td><td>Management personnel from Site A</td></tr><tr><td>P3</td><td>Safety & Security representative from Site B</td></tr><tr><td colspan="2"><strong>Phase 3: Evaluative Study (n=7)</strong></td></tr><tr><td>P4</td><td>An individual drone technology expert with biomass power plant experience.</td></tr><tr><td>G1 (n=4)</td><td>A group from Site A including management, digital management, and safety personnel (included P2).</td></tr><tr><td>G2 (n=2)</td><td>A group from Site B consisting of safety and security representatives (included P3).</td></tr></tbody></table>

## 3.1 Phase 1: Formative Study - Understanding Context and Eliciting Needs

In the initial phase, our aim was to understand the operational context in a power plant through remote semi-structured interviews with stakeholders, such as technical managers, or safety-and-security representatives. To ground these interviews in concrete situations we utilized a video prototype (Fig. 2) and storyboards. We presented these scenarios to participants using a combination of storyboards and an interactive video prototype to simulate key interactions and explore initial design ideas. Video artifacts and prototypes [46, 47] have been used in early HCI studies to evaluate future technologies like a simulated listening typewriter [22]. We created a custom simulation interface as shown in Figure 2 for dynamic mixing of pre-recorded drone footage with audio advisories, giving participants an experiential sense of the proposed concepts. This hybrid technique, using artifacts as contextual prompts, served to ground discussions and gather rich qualitative feedback on safety challenges, communication protocols, and the viability of a drone-based advisory system. Data from these sessions, including interview responses and reactions to simulations, were transcribed and analyzed using Braun and Clarke's thematic analysis inductionally [10] to identify core themes related to user needs, situational constraints and technological opportunities.

<figure><img src="image_4.png" /><figcaption>Figure 2: The video prototype interface used in our formative study (Phase 1), simulates drone interactions for stakeholders by combining drone video feeds with pre-recorded or text-to-speech voice advisories.</figcaption></figure>

## 3.2 Phase 2: From Formative Insights to System Concept

The themes from our formative study provided an empirical foundation for the system concept. Synthesizing these insights, we translated the identified user needs and contextual challenges directly into the design of a concrete, three-part interaction flow for the “Intelligible Drone Advisory System.” To structure the subsequent on-site evaluation, we employed a scenario-based design approach [12]. The interaction flow was solidified into three distinct scenarios (detailed in Section 4.2), designed to test baseline compliance, user confusion, and willful non-compliance. These scenarios were then visualized using storyboards—an effective technique for demonstrating system interfaces and contexts of use [72]—for the subsequent evaluative study (Phase 3).

## 3.3 Phase 3: Evaluative Study - On-Site Technology Probe

The final phase involved on-site visits to evaluate the system concept with staff at two biomass power plants. For this, we employed a technology probe methodology, which uses simple and flexible artifacts to understand user needs and inspire new design ideas in a real-world setting [30]. Our technology probe consisted of a functional drone prototype to demonstrate the auditory experience, used in conjunction with storyboards that guided participants through the interaction scenarios.

The prototype was a DJI Mavic 2 Enterprise Advanced drone equipped with its stock speaker module. We managed the audio advisories using the legacy application on the DJI Smart Controller, which allowed us to upload pre-recorded audio files and play them on demand through the drone's speaker. During the study, we combined the physical drone demonstration with the specific scenario storyboards to conduct a guided walkthrough of the three scenarios. This approach allowed us to gather rich qualitative data through in-situ interviews, direct observation, and contextual
<figure><img src="image_5.png" /><figcaption>Figure 3: A session during our on-site evaluative study (Phase 3) conducted at one of the partner biomass power plants. Plant personnel are gathered to experience the technology probe, discuss the interaction scenarios, and gather feedback.</figcaption></figure>

discussions to assess the usability, and social acceptability of the proposed voice-based drone interactions.

# 4 Results

The results are presented in two parts, mirroring our research process: first, the themes and design considerations derived from the formative study (Phase 1), second, the scenarios (Phase 2), and finally, the user feedback from the evaluation of the resulting system concept (Phase 3).

## 4.1 Formative Study Findings: Key Themes

The inductive thematic analysis of the stakeholder interviews revealed five core themes that encapsulate the primary challenges and opportunities for a drone-based safety advisory system in a power plant environment. These themes formed the empirical foundation for our design.

(1) **Augmenting Situational Awareness:** This theme reflects the need to enhance the control room's real-time understanding of plant-wide events. The drone was envisioned as a mobile sensor that could investigate alarms and provide crucial context that static cameras cannot, especially when control-room operators are tasked with multiple duties.

(2) **Bridging Communication Gaps:** This theme focuses on the drone's role as a dynamic communication bridge to overcome the shortcomings of non-targeted alarms (like sirens) and the logistical hurdles of human face-to-face interaction. The drone is seen as a conduit for delivering clear, direct, and context-specific messages.

(3) **Improving Operational Efficiency:** This theme centers on the drone's ability to overcome the significant physical and procedural frictions of operating in a large-scale facility. It highlights the potential savings in time and human effort by delegating tasks of movement and verification to an automated agent.

(4) **System Design and Implementation Considerations:** This theme encapsulates the crucial human-centered requirements for the system to be effective and trustworthy. It covers

practical aspects such as the need for operator control, system accountability through logging, and the socio-technical challenges of introducing an autonomous agent into the workplace.

(5) **Navigating the Auditory Landscape:** This theme addresses the dual role of sound. First, it covers the challenges posed by the existing noisy environments and alarm fatigue, and second, as the design requirements for creating effective, attention-grabbing alerts and clear voice instructions without adding to the sensory overload.

## 4.2 System Interaction Flow and Design Rationale

The themes from the formative study directly informed the design of a concrete, three-part interaction flow for on-site evaluation. The design of each scenario was justified by the specific needs and key themes we identified, creating a system with tiered responses for baseline compliance, user confusion, and non-compliance to illustrate the progressive escalation of situation criticality from low to high.

<figure><img src="image_6.png" /><figcaption>Figure 4: Scenario 1 - Baseline Compliance. This flow represents the ideal interaction path where the drone identifies a missing piece of Personal Protective Equipment (PPE), delivers a concise voice advisory, and the worker confirms via a simple hand gesture (thumbs-up) before departing.</figcaption></figure>

### 4.2.1 Scenario 1: Baseline Compliance.
This scenario (Figure 4) tested the ideal interaction for a low-risk PPE reminder, a situation where a worker has forgotten a piece of standard protective equipment (e.g., a safety helmet or safety glasses) in an area without immediate, life-threatening danger. To be perceived as non-threatening, the drone's design incorporates an **Introduction Protocol**, approaching with a gentle trajectory and an audible chime as suggested by prior literature [13, 77]. It then delivers a **Structured, Predictable Message** to reduce cognitive load [44]. To fulfill a Phase 1 stakeholder requirement for system accountability, the interaction uses **Closed-Loop Confirmation** by requesting a "thumbs up" gesture, a common modality in HDI [26], to ensure the advisory was understood before the drone departs.

### 4.2.2 Scenario 2: User Confusion.
This scenario (Figure 5) addressed situations where a user is willing but unable to comply. If a user signals a problem (e.g., "thumbs down"), the system interprets it as a request for help rather than defiance. This choice was made to build **Trust and Social Acceptability** [15]. The drone then instructs the user to contact a support agent, solving the issue and
<figure><img src="image_7.png" /><figcaption>Figure 5: Scenario 2 - User Confusion. This scenario is designed for situations where a user is willing but unable to comply. Upon receiving a gesture for requesting help (thumbs-down), the system instructs the user to contact a human support agent, avoiding unnecessary escalation while still resolving the problem.</figcaption></figure>

enabling flexibility in communication. This allows minor issues to be resolved efficiently without involving senior safety officers, a key aspect of the system's **Tiered Escalation** logic (i.e., matching the response intensity to the severity of the situation), which is important in managing emergency communications [49].

4.2.3 **Scenario 3: Escalation for Non-Compliance.** This scenario (Figure 6) handles critical violations with a non-negotiable, **"Comply First, Question Later"** model. The drone first issues a firm command using a sharp, urgent auditory alert to convey criticality [39]. If ignored, the system's **Tiered Escalation** logic alerts a human Safety Officer for live voice intervention. This provides a **Human-in-the-Loop for Final Authority**, a key requirement in critical HRI systems to ensure compliance in serious situations [31, 63].

<figure><img src="image_8.png" /><figcaption>Figure 6: Scenario 3 - Escalation for Non-Compliance. For critical violations, the system follows a tiered protocol. The system first issues an automated, high-priority command. If ignored, it alerts a human Safety Officer to engage directly, using their authority as a last resort for compliance.</figcaption></figure>

## 4.3 Evaluative Study

The study employed a multi-stage methodology, progressing from foundational user understanding to on-site visits and field studies. The scenarios were designed to evaluate the system's core functionality, its ability to handle user confusion, and its response to willful non-compliance. The study was conducted with operational personnel in several biomass power plants.

4.3.1 **Scenario 1: Baseline Compliance and First Impressions.** This scenario, focusing on a simple PPE reminder, elicited detailed feedback on the fundamental aspects of the drone's presence, voice, and interaction style.

**Approach: Sound and Trajectory Must Signal Intent Without Alarm-ing.** Participants unanimously agreed that a drone should make sound during its approach to signal its presence and intent, as a silent approach was perceived as unsettling or unsafe. There was a preference for sounds that were noticeable but not alarming, such as “harmonics of the major scale” (G1) or a “Public-Address-like sound” (G2) designed to stand out from background machinery noise. The drone’s physical approach was also critical. A direct, eye-level trajectory was seen as potentially aggressive, whereas a “gentle descent” or an “L-shaped trajectory” was perceived as friendlier and less distracting (G2).

<figure><img src="image_9.png" /><figcaption>Figure 7: Participants provided feedback on drone approach trajectories involving hand-gesture expression. A direct approach at eye level was seen as possibly aggressive and confrontational.</figcaption></figure>

**Voice: Perceived Conflict Between Clarity and Authority.** The voice persona of drone generated significant discussion. Several participants preferred a female voice, noting its higher pitch could cut through low-frequency machinery noise and was perceived as “aut authoritative yet less aggressive” (G2). However, another participant (P4) found the female voice “too exciting” and not serious enough for an industrial setting, preferring the male voice’s tonality. The consensus was that regardless of gender, the tone must be professional and avoid sounding “too happy or chirpy” to be taken seriously.

**Interaction: Clarity in Commands and Feedback Matters.** The “thumbs up” gesture was seen as a simple and universally understood way to acknowledge an instruction. However, one expert (G2) critiqued offering a “thumbs down” option in a safety compliance context, arguing it “implies a choice rather than a non-negotiable order.” The participant advocated for triggering escalation when a user does not provide a directive command, such as “thumbs up to acknowledge”. Similarly, feedback at the end of an interaction needed to be clear but professional. A simple “ending chime” was considered helpful, but a more melodic, “happy tune” (a major-scale tone) was negatively received, with one participant comparing it to an “ice cream truck,” which felt inappropriate for a safety context (P4).

4.3.2 **Scenario 2: Assisting Confused Users.** This scenario explored the system's ability to gracefully handle situations where users were willing but unable to comply due to confusion.
*Drone as a Guide and Helper.* Participants valued the system's ability to offload simple queries from the main control room to autonomous agent between drone and the user. One manager (G2) gave a real-world example where a contractor's confusion during a fire drill led to a one-hour evacuation delay for over 100 people, emphasizing the immense value of a drone that can quickly enforce messages and avoid physical 15-minute trips between control room and target for human operators (G1). When providing assistance, participants suggested the drone could guide a user to a prearranged intercept point with human staff. For safety, they also advised that a lost or stuck person should be instructed to “stay put” while help is dispatched, preventing them from wandering into further danger.

*Integration with Existing Systems and Workflows.* For the system to be adopted by control room operators, seamless integration is key. One participant stressed that it should function as a “moving camera” within their existing VMS, not as another separate screen that would increase cognitive load (G1). This “flying CCTV” concept was seen as a natural extension of their current tools.

### 4.3.3 Scenario 3: Escalation for Non-Compliance.
This scenario tested the system's tiered response to a user willfully entering a restricted zone, dismissing authority and enforcement.

*Conveying Urgency and Authority through Sound and Movement.* The use of a “sharp beep,” for the restricted zone warning was seen as highly effective at communicating urgency and demanding immediate attention (G1, G2). Participants agreed that the system must use different sounds for different levels of criticality. This sense of being monitored was not just auditory; it was suggested that during an escort out of a restricted area, the drone should fly backward to maintain constant visual contact. This “eyes on them” behavior was seen as a key physical action to apply authoritative pressure and ensure compliance.

*Non-Negotiable Instructions and Human-in-the-Loop.* For critical safety violations, participants insisted that the interaction should “not be a negotiation” (G1). The instruction must be a clear, direct command to leave the area immediately. They argued that even in the case of a false positive, personnel should comply first and ask questions later. The final escalation step, a live voice passthrough from a human Safety Officer, was seen as essential. Hearing a human voice was perceived as creating a much stronger sense of being watched and would be more effective at compelling compliance than a purely automated system.

*Social Benefit: Mitigating Interpersonal Confrontation.* An important emerging finding was the social value of using a robot as an intermediary. G2 noted the system would be “really great to mitigate the confrontation” that can occur when safety staff have to correct their colleagues for minor, unintentional infractions. By automating the initial reminder, the drone reduces interpersonal friction and helps maintain a more positive safety culture.

## 5 Discussion

The on-site evaluation of our drone-based advisory system provided several key insights into the design of effective human-drone interaction for safety compliance in industrial environments. Our findings on the drone's perceived authority, communication structure,

and workflow integration reinforce the importance of designing for safe and empowering human-robot collaboration in industrial environments [32, 58]. In this section, we synthesize these findings into a set of actionable design implications for future systems, before discussing the limitations of our study and avenues for future work.

### 5.1 Implications for Design

Our findings from the on-site evaluative study lead to a set of design implications for future Human-Drone Interaction in safety-critical, industrial environments. We group these into three key areas: designing the drone's physical and vocal presence, structuring the interaction for safety, and integrating the system into existing human workflows.

#### 5.1.1 Designing for Perceptual Clarity and Authority.
The drone must be perceived as an official, authoritative, and non-threatening entity. This is achieved not just through its voice, but through its entire physical presence [50, 70, 76].

*Sonify the Approach to Signal Intent.* A silent drone approach was perceived as unsettling and unsafe. Our findings and prior work [1, 3, 14, 53] strongly indicate that drones should use sound to announce their presence and purpose (Figure 1). These sounds should be noticeable over background noise but designed to be informative rather than alarming [20], such as a “Public-Address-like sound” or simple harmonics. This aligns with research in sonic interaction design, which aims to create sounds that are useful information rather than distracting noise [5, 57], and fits into the broader study of soundscapes within Human-Computer Interaction [37]. Rather than simply masking the inherent, consequential sounds of the drone’s operation, these sounds can be captured and modified to serve as a creative and communicative material [34, 35].

*Utilize Drone Kinematics to Convey Authority.* A robot's movement is a powerful communication tool [36]. In our study, a gentle, indirect “L-shaped” trajectory was perceived as friendlier and less confrontational than a direct, eye-level approach, a finding consistent with studies on human-robot proxemics [68]. Conversely, in an escalation scenario, the act of flying backward to maintain constant visual contact between the human operator and the drone was seen as a key behavior to apply authoritative pressure and convey a sense of being monitored. This uses the drone’s movement to enhance situational awareness for the human, which is an important part of effective human-robot interaction. [16].

*Prioritize an Authoritative yet Calm Voice Persona.* The drone's voice must balance authority with clarity, as the interaction's context is key to how a robot's voice is perceived as appropriate [70]. While participants often preferred a female voice for its higher pitch, which they noted could cut through low-frequency machinery noise, this preference should be viewed within the site's male-dominated social context. Research confirms that vocal characteristics such as gender and prosody significantly influence the trust a user places in a robot [50, 71]. Irrespective of the specific voice, the key element was a professional and serious tone, not one that was “too happy or chirpy,” to be taken seriously. This supports findings that in emergencies, direct and urgent communication styles are
more effective and perceived more positively than overly polite or
casual tones [39].

**5.1.2 Structuring the Interaction for Safety and Efficiency.** The logic of the interaction must prioritize unambiguous communication and fail-safe procedures [9].

Employ a *Tiered System of Auditory Alerts*. A one-size-fits-all alarm is ineffective. The system should use a lexicon of sounds, reserving sharp, urgent cues (like a “truck reversing” beep) for critical, high-priority events like entering a restricted zone, while using softer tones for standard advisories. This approach, using distinct auditory icons or “earcons,” is a well-established method in auditory information design for conveying different types of information effectively [11, 20]. The perceived danger and urgency of sounds can be mapped to specific musical and acoustic features, allowing for the creation of a clear auditory hierarchy [7, 59].

Adopt a *“Comply First, Question Later” Model for Critical Instructions*. In safety-critical situations, ambiguity is dangerous [49]. Instructions should be non-negotiable commands, not suggestions, to ensure progressivity and accountability in the interaction [19, 43]. For example, acknowledgment should be an imperative (“Give a thumbs up to acknowledge”) rather than a choice, with any non-compliance leading directly to escalation. This contrasts with politeness strategies often effective in non-critical scenarios [66], high-lighting that communication in emergencies requires a different, more direct approach [39].

Ensure a *Human-in-the-Loop for Final Authority*. While the drone handles initial interactions, the final authority should rest with a human. The live voice passthrough from a Safety Officer was seen as the most powerful tool for compelling compliance in a serious situation, creating a stronger sense of being watched than a purely automated system could achieve. This aligns with established models of human-robot collaboration where humans assist robots in abnormal or complex situations [31]. A human-in-the-loop approach allows humans to maintain a crucial role, particularly for decision-making and establishing trust [15, 63].

**5.1.3 Integrating the System into Human Workflows.** For a system to be adopted, it must solve real problems for the staff without creating new ones.

*Drone as a Neutral Intermediary and Agent*. One of the most significant benefits identified was the drone's ability to act as a neutral intermediary. It can reduce interpersonal friction between colleagues by automating routine safety corrections and can resolve simple issues (like helping a confused operator), freeing up the control room's time and attention for more critical tasks. This establishes the drone not merely as a tool, but as a social actor that depersonalizes safety enforcement. This role reflects that robots can mediate and reshape social dynamics within a work environment [33], hence allowing human personnel to focus on higher-level monitoring and decision-making [73].

*Design for Integration, Not Isolation*. To avoid overwhelming operators, the drone's interface should not be yet another screen to watch. The system should be seamlessly integrated into existing control room software (e.g., the VMS), functioning as a controllable

*“flying CCTV” or a mobile extension of the tools they already use. This addresses the challenge of managing an “ecology of screens” and reducing cognitive load, which is critical for operators supervising multiple systems [2, 27]. By framing the drone as an extension of existing monitoring tools, it can be more readily adopted into established workflows for tasks such as remote inspection [21, 28].*

**5.2 Limitations and Future Work**

This study has limitations inherent to its formative nature. Our findings are based on a Wizard-of-Oz (WoZ) prototype with a focused sample of expert personnel. While this provided deep contextual insights, it does not fully represent the diversity of external contractors. Additionally, while we designed for auditory clarity, we did not perform a formal quantitative evaluation of speech intelligibility in the acoustic field. Crucially, this study captures initial user reactions. Long-term deployment is required to understand habituation and the potential for the “eye in the sky” effect to erode trust over time. Future work should focus on longitudinal “in-the-wild” deployments to assess these temporal dynamics and validate the system’s effectiveness across broader demographics and industrial contexts.

**6 Conclusion**

Ensuring the safety of personnel in large-scale infrastructure is challenging, especially for external staff who may be overlooked by formal communication systems. This paper addresses this gap with a user-centered design and evaluation of a drone-based system delivering clear voice advisories. Our research, based on safety personnel experiences, led to a functional prototype. Our main contribution is a set of design considerations for creating a drone seen as an authoritative but non-threatening safety agent. We showed the importance of using sound for intent, kinematics for authority, and a clear voice persona. We proposed a tiered interaction model for managing user confusion and escalating non-compliance, with human oversight. Surprisingly, the drone also serves as a neutral intermediary, reducing interpersonal friction in safety enforcement. As autonomous systems become common, designing for effective, socially acceptable interaction is essential. Our work offers a practical framework for human-drone interaction in safety-critical fields, ensuring these systems are useful and humane.

**Acknowledgments**

This work was supported in part by the Innovation Fund Denmark for DIREC project U07 (the PERSIST project), and the Independent Research Fund Denmark under grant 10.46540/4264-00105B (the NAMUR project). Morevoer, we gratefully acknowledge the financial support provided EDSYS Doctoral School and Afihm through their Mobility funding programs.

The authors used Generative AI (Gemini) in order to improve language and readability. Some illustrative elements in figures 1, 4, 5, and 6 were generated using AI-based image creation tools; these elements were then selected, composed, and arranged by the authors to create the final figures that support the paper's narrative. The authors reviewed and edited all content as needed and take full responsibility for the content of the publication.
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Received 2025-09-30; accepted 2025-12-01