Cloud-Enabled Indoor Thermal Comfort Assessment and Visualization Using Digital Twins, IoT, Robotics, and Indoor Positioning Technology

Abstract

Thermal comfort plays a critical role in ensuring the health and productivity of occupants. However, it is difficult to dynamically assess the thermal comfort at heterogeneous locations because (1) conventional methods merely rely on measurements taken by thermal sensors placed at designated/fixed positions, and (2) many existing facilities still rely on 2D as-built drawings, resulting in low interoperability between the dynamic thermal condition information and the 2D plans. To address these challenges, this paper proposes a framework that integrates digital twins, IoT (Internet of Things), robotics, and indoor positioning to better support real-time thermal comfort assessment and visualization in as-built facilities. The following steps were conducted: (1) constructing a 3D virtual digital twin representation of a facility, (2) creating a smart thermal sensing unit to measure the real-time air temperature and relative humidity using IoT-enabled devices, (3) configuring an unmanned ground vehicle (UGV) (i.e., a robot) to enable the mobility of the sensing unit by autonomously navigating to different locations, and (4) developing an indoor positioning system for assisting in dynamically visualizing the thermal condition in the created 3D digital twin. The developed framework was tested in a real-world application at the authors’ institution to validate its applicability and performance. The results showed that the proposed framework has satisfying performance on real-time thermal condition assessment and visualization. Ultimately, this paper contributes to the body of knowledge by offering a novel thermal comfort assessment and visualization system through integrating digital twins, IoT, robotics, and indoor localization to facilitate smarter facility management.