Understanding social behaviors in the indoor environment a complex network approach

Abstract

Being able to monitor and analyze human interactions in the indoor environment over time has many architectural applications from spatial planning to post occupancy evaluation. In this paper, we present our interdisciplinary approach that interprets human-spatial interactions as a complex network. We combine methods and techniques from sensor networks, signal processing, data mining, network theory, and information visualization to form a novel framework that facilitates versatile investigations. We will demonstrate the framework with a real-world case study: we have collected and analyzed human-spatial interaction data from a workshop scenario where multiple design projects were conducted within a shared studio space.