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Research Challenges for Adaptive Architecture: Empowering Occupants of Multi-Occupancy Buildings

Binh Vinh Duc Nguyen, Andrew Vande Moere

TL;DR

The paper tackles the challenge of making multi-occupancy buildings more responsive to occupants by proposing adaptive architecture that uses robotic furniture and semi-autonomous partitions to reconfigure spaces. It introduces a sense‑of‑place model, composed of spatial, situational, and subjective qualities, to guide when and how adaptations should occur, aiming to maintain occupant comfort, health, and wellbeing. The authors delineate a tri-level research agenda—addressing individual experiences, mediating collocated interactions, and engaging building communities—with strategies such as privacy-preserving sensing, shared autonomy, and participatory design. If realized, this approach could transform design practices and building management, enabling dynamic, transparent, and health-promoting environments in dense urban settings.

Abstract

This positional paper outlines our vision of 'adaptive architecture', which involves the integration of robotic technology to physically change an architectural space in supporting the changing needs of its occupants, in response to the CHI'24 workshop "HabiTech - Inhabiting Buildings, Data & Technology" call on "How do new technologies enable and empower the inhabitants of multi-occupancy buildings?". Specifically, while adaptive architecture holds promise for enhancing occupant satisfaction, comfort, and overall health and well-being, there remains a range of research challenges of (1) how it can effectively support individual occupants, while (2) mediating the conflicting needs of collocated others, and (3) integrating meaningfully into the sociocultural characteristics of their building community.

Research Challenges for Adaptive Architecture: Empowering Occupants of Multi-Occupancy Buildings

TL;DR

The paper tackles the challenge of making multi-occupancy buildings more responsive to occupants by proposing adaptive architecture that uses robotic furniture and semi-autonomous partitions to reconfigure spaces. It introduces a sense‑of‑place model, composed of spatial, situational, and subjective qualities, to guide when and how adaptations should occur, aiming to maintain occupant comfort, health, and wellbeing. The authors delineate a tri-level research agenda—addressing individual experiences, mediating collocated interactions, and engaging building communities—with strategies such as privacy-preserving sensing, shared autonomy, and participatory design. If realized, this approach could transform design practices and building management, enabling dynamic, transparent, and health-promoting environments in dense urban settings.

Abstract

This positional paper outlines our vision of 'adaptive architecture', which involves the integration of robotic technology to physically change an architectural space in supporting the changing needs of its occupants, in response to the CHI'24 workshop "HabiTech - Inhabiting Buildings, Data & Technology" call on "How do new technologies enable and empower the inhabitants of multi-occupancy buildings?". Specifically, while adaptive architecture holds promise for enhancing occupant satisfaction, comfort, and overall health and well-being, there remains a range of research challenges of (1) how it can effectively support individual occupants, while (2) mediating the conflicting needs of collocated others, and (3) integrating meaningfully into the sociocultural characteristics of their building community.
Paper Structure (7 sections, 2 figures)

This paper contains 7 sections, 2 figures.

Figures (2)

  • Figure 1: Our series of empirical studies with architectural-scale, semi-autonomous mobile robotic partitions that adapt the layouts Nguyen2020 of multi-occupancy homes Nguyen2021 or offices Nguyen2022Nguyen2024.
  • Figure 2: Our sense of place model, demonstrating how the occupant perception of a temporally-adapted layout hinges on the holistic alignment of its spatial, situational, and subjective qualities Nguyen2022.