Quantifying Personality in Human-Drone Interactions for Building Heat Loss Inspection with Virtual Reality Training

College

College of Engineering

Department

Construction Management

Publication Date

3-2026

Abstract

Reliable building energy audits are crucial for reducing waste and improving energy efficiency, particularly through the detection of heat loss in building envelopes. While sensor-equipped drones and AI-powered solutions assist in path planning and refining human operators’ control actions, they often overlook the nuanced interplay between personality traits, stress management, and operational strategies that expert engineers employ when adjusting flight paths based on real-time observations. This gap underscores the challenge of achieving accurate and efficient drone-based inspections, necessitating both methodological adjustments and a comprehensive understanding of human cognitive and behavioral factors. Moreover, workforce shortages due to retiring experts necessitate effective knowledge transfer to train the next generation of inspectors. This study proposes a virtual reality (VR)-based workforce training system designed to improve human-drone interaction for building heat loss inspection. Participants piloted a virtual drone equipped with a thermographic monitor to identify defects in a simulated environment. By analyzing flight trajectory patterns, stress adaptation, and inspection performance across trainees with diverse engineering backgrounds and personality traits, we uncovered key insights: 1. Flight Trajectory Patterns – Participants who are Extraverts, Intuitives, Feelers, and Perceivers explored larger areas but exhibited higher misclassification rates, while participants who are Introverts, Sensors, Thinkers, and Judgers demonstrated methodical, structured approaches. 2. Stress Adaptation – Analysis of heart rate variability (HRV) revealed broader stress fluctuations among participants who are Extraverts, Intuitives, Feelers, and Perceivers, whereas Introverts, Sensors, Thinkers, and Judgers maintained steadier physiological responses under demanding tasks. Task complexity further magnified these differences, influencing performance under pressure. 3. Inspection Performance – Participants who are Extraverts, Intuitives, and Feelers achieved higher recall and coverage but were prone to over-identifying non-defective areas. Conversely, Introverts, Sensors, Thinkers, and Judgers made fewer random errors but risked overlooking subtle heat losses. These insights highlight the interplay among personality traits, stress management, and operational strategies in VR-based training for drone-assisted building audits. The proposed framework shows potential for addressing workforce shortages by facilitating tacit knowledge transfer and optimising human–drone collaboration. This study advances adaptive training paradigms for the evolving demands of intelligent building diagnostics.

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