Mobiusi/Open-Office-Workstation-Usage-Detection-Dataset

Open Office Workstation Usage Detection Dataset

A major core advantage of this dataset is its data quality. The annotation process ensures more than 95% accuracy and consistency, covering various lighting conditions and office scenarios. Its technological innovation lies in the use of advanced image enhancement techniques, significantly improving the training effectiveness of detection models. In terms of application value, models trained with this dataset can increase the accuracy of workstation utilization analysis by more than 20% and save over 30% in management costs compared to traditional methods. Compared with other workstation detection datasets, this dataset has outstanding advantages in terms of data volume and diversity, especially with its complete data flow and multi-time period coverage. Unique data features include full coverage of dynamic changes and advanced capabilities for handling complex backgrounds. The dataset structure is optimally designed to support subsequent expansion to other commercial space usage scenarios, and its versatility ensures effective applicability in various office environments.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
occupancy_status	string	Indicates whether the workstation is currently occupied or vacant.
number_of_people	int	The number of people detected within the office area in the image.
desk_count	int	The total number of workstations visible in the image.
lighting_condition	string	The lighting condition within the office, e.g., bright, moderate, dim.
seating_arrangement	string	The arrangement of the workstations, such as open-plan or partitioned.
equipment_count	int	The number of visible equipment in the office area, such as computers, phones, etc.
personal_items_count	int	The number of personal items visible on the workstations, such as mugs, sticky notes, etc.
noise_level	string	The likely noise level as judged visually, such as quiet, moderate, noisy.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com