Tracking Real-Time Energy Demand Consumptions Using Urban Activity Data
Toward a smart community design, we propose a new GeoDesign approach using real-time urban activity data. It is an important topic to establish a GeoDesign method considering real-time energy demand monitoring system for creating energy resilient smart clusters of individual buildings. Fortunately, an increasing number of individual building information are acquired though most of them are not available for researchers yet. Given these backgrounds, this study attempts to use micro geo-data, including (i) Google's Populartime data and (ii) an IoT sensor data, to estimate individual building energy demands in the city center of Tokyo. (i) The Populartime data is a collection of aggregated and anonymized location history of smartphone users. The data reveals relative population density/congestion in individual shops, restaurants, and other customer facilities, by hour by week. Regarding (ii), we installed an IoT sensor, which records people entering and leaving, into buildings. We estimate the hourly population density/congestion in each commercial building based on both data. The result suggests that spatial BigData are useful for real-time urban energy monitoring.