Screenshot: Datenmaschine - Location data

With building stock being one of largest expenses after staff costs, it is imperative to understand the interaction of staff, students and space. Providing the right spaces at the right time is essential for a good teaching and learning experience.

Student Experience

The timetable can provide information about the planned occupancy, but understanding the ratio between planned and actual occupancy is the key information necessary for efficient space planning.

Datenmaschine can be configured to show the actual attendance rate, preferred places outside of timetabled hours, trip pattern and overall dwell times on campus.

When it comes to popular places, people vote with their feet.

A detailed understanding, how current activities are spread across the various buildings and how often and how long these places are visited, is essential to identify over- or under-utilised spaces.

Wireless data has a high accuracy in enclosed spaces (e.g., lecture theatre occupancy can be measured with an accuracy of > 95%), allowing direct insight into the usage of different types of spaces. Space capacity and actual occupancy can be correlated over longer time periods (for example a semester) and will show preferred time slots (e.g., morning vs afternoon, Monday vs Friday, etc.) and attendance rate fluctuations.

Detailed information about the current utilisation allows more efficient infrastructure planning and will improve the campus experience for students, staff and visitors.

Screenshot - Datenmaschine