The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach

With the advancement of Internet Things (IoT) and communication platform, large-scale sensor deployment can be easily implemented in an urban city to collect various information. To date, there are only a handful research studies about understanding usage public spaces. Leveraging IoT, sensors have been deployed residential area monitor study space utilization patterns. In this article, we propose data processing system generate space-centric insights region multiple Points Interests (PoIs) that consists 190 000 m 2 real estate. We identify activeness each PoI based on spectral clustering, then their corresponding static features, which composed transportation, commercial facilities, population density, along with other characteristics. Through heuristic features inferring, density facilities most significant factors affecting place utilization.