Abstract
Highlights: What are the main findings? Unplanned social interactions between people are detectable in spatio-temporal lidar streams with 86.1% precision. These social interactions are related to but spatially and temporally distinct from simple measures of occupancy. What is the implication of the main finding? These methods can be used for post-occupancy evaluation of indoor spaces designed to facilitate social interaction. Indoor environments significantly influence human interaction, collaboration, and well-being, yet evaluating how architectural designs actually perform in fostering social connections remains challenging. This study demonstrates the use of 11 static-mounted lidar sensors to detect serendipitous encounters—collisions—between people in a shared common space of a mixed academic–residential university building. A novel collision detection algorithm achieved 86.1% precision and detected 14,022 interactions over 115 days (67 million person-seconds) of an academic semester. While occupancy strongly predicted collision frequency overall (R2 ≥ 0.74), significant spatiotemporal variations revealed the complex relationship between co-presence and social interaction. Key findings include the following: (1) collision frequency peaked early in the semester then declined by ~25% by mid-semester; (2) temporal lags between occupancy and collision peaks of 2–3 h in the afternoon indicate that social interaction differs from physical presence; (3) collisions per occupancy peaked on the weekend, with Saturday showing 52% higher rates than the weekly average; and (4) collisions clustered at key transition zones (elevator areas, stair bases), with an additional “friction effect”, where proximity to seating increased interaction rates (>30%) compared to open corridors. This methodology establishes a scalable framework for post-occupancy evaluation, enabling evidence-based assessment of design effectiveness in fostering the spontaneous interactions essential for creativity, innovation, and place-making in built environments.
| Original language | English |
|---|---|
| Article number | 3236 |
| Journal | Remote Sensing |
| Volume | 17 |
| Issue number | 18 |
| DOIs | |
| State | Published - Sep 2025 |
Keywords
- indoor geography
- lidar
- movement tracking
- post-occupancy evaluation
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