NSF Award
2425121
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.<br/><br/>Facilities operations encompass a wide range of essential services, such as ensuring occupant thermal comfort, energy management, and overseeing space design and management. Public and commercial enterprises, such as healthcare facilities, schools, and community centers, must confront the rising costs of operating their facilities every day. For such enterprises, the most significant and costly operations inefficiencies arise from an inability to accurately predict facilities usage, which can be highly dynamic and uncertain. This project pioneers a new approach to modeling and predicting human-infrastructure interactions, behavior, and decision making within facilities, to address the inefficiencies that often arise from these factors. By developing a Human-centric Intelligent Facilities Integration framework that combines real-time sensing, computational modeling, and automated decision making tools, facilities management will be moved from a conventional, operational focus to a dynamic, human-centered approach. Using this framework, facilities will be able to proactively adapt to and anticipate the needs and behaviors of their users, fostering more inclusive, sustainable, and efficient environments. These models will empower cities to better prioritize investments and target specific outcomes, as facilities are one of the most important elements needed to start and maintain transformation of deindustrialized centers.<br/><br/>Despite their integral role, there is limited understanding of how human interactions impact facilities and how this knowledge could enhance efficiency, utilization, and resource distribution. Progress requires creating interdisciplinary opportunities for computational behavioral research to integrate with engineering for measurement, prediction, and automation. This project’s Human-centric Intelligent Facilities Integration framework addresses this challenge by bridging three fields: behavioral and cognitive science, cyber-physical systems, and design. This research develops new cognitive models to represent psychological decision making in the context of facility usage, focusing on how individuals interact with and navigate through physical and social spaces. These models are contextualized by dynamic instances and features not previously studied in highly dynamic facility environments. New privacy-preserving technologies are developed to map spatio-temporal social interaction data into existing facility management digital infrastructure. Finally, a novel hierarchical, learning-based model fusing cognitive, social, and spatial layers is developed for predictive modeling of human adaptations to changes in facilities management. The project also generates valuable datasets that document human-infrastructure interactions in facilities, allowing other researchers to further advance understanding. Additionally, the project provides open-source tools and implementations of various framework components to facilitate replication and collaboration within the scientific community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
