Researchers at Osaka University have developed a novel framework that measures open-plan office occupancy with unprecedented accuracy. This innovative system leverages computer vision and artificial intelligence to analyze occupancy in specific functional areas of offices at a micro level. The findings were published in the Journal of Building Engineering.

Current occupancy tracking methods have significant limitations, typically providing only macro-level data and failing to capture detailed usage patterns in shared spaces. Open-plan offices have an urgent need for more granular and accurate occupancy information, as traditional approaches cannot reflect the complexity of space utilization, leading to inefficient resource allocation and design. The new framework offers a practical and cost-effective solution that collects fine-grained occupancy data, providing evidence-based insights for office design and management decisions to create more sustainable, efficient, and human-centered workspaces.

The researchers utilized existing CCTV cameras and 3D pose estimation technology to build a computer vision system capable of precisely measuring micro-level occupancy in designated functional zones of open-plan offices. The system tracks individuals by analyzing video segments, classifies their positions within predefined areas, and aggregates the data to reveal occupancy patterns.

Real-world testing confirmed the system's accuracy and provided valuable insights into how employees use different office zones. These findings can inform decisions on office layout, resource allocation (lighting, heating, cleaning), and energy management, contributing to more efficient and sustainable workplaces.

PhD student Sihua Chen, involved in the study, highlighted the project's interdisciplinary nature, combining environmental engineering with computer science to address real-world challenges. She noted that this technology has the potential to fill gaps in existing occupancy measurement methods and provide data-driven support for the sustainable design and operation of indoor open-plan office spaces.

The research holds significant implications for the future of office space design. By delivering precise and detailed occupancy data, it enables data-driven optimization of office layouts, resource allocation, and energy control, fostering more sustainable and efficient work environments.