An Empirical Evaluation of an Occupancy-Based IoT Control Deployment for Lighting and HVAC in an Office Environment

Energy-intelligent building control is widely advocated as a key strategy for reducing building energy use and associated carbon emissions. However, empirical evidence from real buildings remains relatively scarce and is often affected by methodological limitations. This study reports a 92-day field experiment on the 14th floor of an office building in Shenzhen, China, where an Internet of Things (IoT) and edge-computing-based intelligent building environmental control system was deployed to manage lighting and HVAC. An A-B-A experimental design was implemented in summer 2022, comprising two intelligent-control phases (A₁ and A₂, July and September) and one intermediate manual-control phase (B, August) during which the intelligent algorithms were disabled without notifying occupants. Aggregated monthly runtimes show average energy-saving potential ratios of approximately 25.98% for lighting and 19.50% for HVAC when the intelligent system is active. As this study was conducted on a single office floor in one building, the results should be interpreted as proof-of-concept field evidence for this specific operational and climatic context rather than as directly generalizable performance estimates for all office buildings. The study further highlights methodological considerations for future field evaluations, including the influence of outdoor climate, occupancy patterns and experimental design choices. The findings provide a real-world empirical case of the energy-saving potential performance of intelligent environmental control in office buildings and contribute to narrowing the gap between simulated and measured savings.