UGV-Based Spatiotemporal Monitoring of Indoor Environmental Quality Using an Integrated BIM-IoT Framework with Autonomous Navigation

Résumé fourni par la source

Indoor Environmental Quality (IEQ) monitoring is essential in smart buildings to ensure occupant comfort, enhance productivity, and support well-being. Traditional monitoring methods use a limited number of stationary sensors, which restrict spatial coverage due to high infrastructure and maintenance costs. To address this limitation, we propose a mobile sensing system using an Unmanned Ground Vehicle (UGV) for high-resolution spatial and temporal IEQ monitoring within indoor spaces. The UGV integrates Ultra-Wideband (UWB)-based localization, Building Information Modeling (BIM), Simultaneous Localization and Mapping (SLAM), and autonomous navigation for efficient mobility and obstacle avoidance. The system is designed to collect temperature, humidity, and carbon dioxide (CO2) parameters. The study is conducted in a controlled office environment and compared with a stationary sensor network. Inverse Distance Weighting (IDW) interpolation method is applied to generate thermal maps from the collected data. The UGV achieves positional accuracy within ±6–8 in., sufficient for precise spatial mapping. The resulting maps have a spatial resolution of 1–1.5 ft, offering finer detail than conventional methods. This mobile approach provides accurate, high-resolution spatial distributions of IEQ parameters in indoor spaces and offers a cost-effective, scalable solution for assessing spatial distribution of indoor environmental variables.

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