Space inference system for buildings using IoT

Youngmin Ji, Woosuk Choi, Kisu Ok, Jooyoung Ahn, Junjae Yoo

Abstract: Korea has continued to receive international pressure on GHG (Greenhouse Gas) reduction as it is the world's seventh-largest GHG emission source, and the government has already submitted to the UN INDCs (Intended National Determined Contributions) to reduce 37% of its GHG emission compared to a Business As Usual (BAU) in post-2020 on June 2015. There are various methods to save energy in order to fulfill this reduction obligation. The most effective methods are to increase the energy efficiency of the building, which accounts for about 30% of the existing energy consumption in Korea. Most of the existing buildings do not use 30% of the building space. To reduce this, a system such as BEMS (Building Energy Management System) is needed to grasp and monitor the environment inside the low-cost buildings. However, most BEMS systems are very expensive, and small-scale buildings are difficult to apply because of the low cost of investment. In this paper, we propose a system for inferring the energy use status of each space by collecting environmental information of existing buildings using IoT device. The IoT sensor uses the temperature, humidity, CO2 (Carbon Dioxide), and PIR (Passive Infrared) sensor to judge whether the thermal comfort of the room and the room is occupied or not, and whether the energy is efficiently consumed by the space. Finally, the intelligent system can utilize the historical data of the inferred occupant to predict the occupancy in advance for the control.