The simulation method uses various factors including the properties of building construction materials, the energy efficiency of related equipment such as air conditioners and lights, and the usage periods to calculate the theoretical energy consumption of a building. By comparing with the real consumption, the energy-saving potential can be determined. Aside from simulation, statistical methods have also been developed to determine energy-saving potential. Chung et al. [12] used multiple regression analysis to build a benchmark table by investigating the relationship between EUIs and explanatory factors. Lee and Lee et al. [13] proposed adjusting the statistical method by using data envelopment analysis (DEA). The research of Lee et al. suggests simplified factors, including scale factors and management factors.

Simplified factors could efficiently investigate the energy-saving potential of government office buildings.Both simulation and statistical methods consider too wide a range of factors to perform a practical investigation, so any survey of energy-saving potential costs money and requires resources for collecting data. In this study, a cloud sensor system is developed for investigating energy-saving potentials. The developed system aims to fulfill the following requirements:Surveying energy-saving potentials only depends on information collected from webpages. This is also called a cloud sensor system.Surveying energy-saving potentials of distributed sites accurately.Identifying sites with low energy-saving potentials.2.

?Cloud Sensor System DevelopmentIn order to meet the above requirements, structured data, an analyzer and a cloud system for initial data input are integrated in this study to develop a cloud sensor system, as shown schematically in Figure 1. As illustrated in the panels from top to bottom on the left side of the figure, the owner of a store or building under investigation registers online Dacomitinib and sequentially inputs the store name, address, area, and customer ID of electricity. This cloud sensor system is applicable to all types of buildings, although the focus of this study is the store application. A store is a building with complex usage purposes. The primary energy consumption includes air conditioning and lighting. Certain stores are equipped with power devices such as elevators or refrigerators.

People work there, pass through, stay for a while, or spend a long time shopping. The complex pedestrian flow and versatile equipment makes energy consumption and saving potential difficult to investigate. This study focused on investigating the energy-saving potential of stores that can be used for other types of buildings if the developed system works.Figure 1.The schematic view of cloud sensor system: The left top panel and following panels show the manual input processes.