Embedded Software Convergence Research Center, Korea Electronics Technology Institute, 68 Yatap-dong, Bundang-gu, Seongnam 463-070, Korea.
Sensors (Basel). 2012 Oct 1;12(10):13458-70. doi: 10.3390/s121013458.
In this paper, we propose a new HVAC (heating, ventilation, and air conditioning) control strategy as part of the smart energy system that can balance occupant comfort against building energy consumption using ubiquitous sensing and machine learning technology. We have developed ZigBee-based wireless sensor nodes and collected realistic temperature and humidity data during one month from a laboratory environment. With the collected data, we have established a building environment model using machine learning algorithms, which can be used to assess occupant comfort level. We expect the proposed HVAC control strategy will be able to provide occupants with a consistently comfortable working or home environment.
在本文中，我们提出了一种新的暖通空调（加热、通风和空调）控制策略，作为智能能源系统的一部分，该策略可以利用无处不在的感测和机器学习技术来平衡居住者舒适度和建筑能耗。我们已经开发了基于 ZigBee 的无线传感器节点，并从实验室环境中收集了一个月的真实温度和湿度数据。利用收集到的数据，我们使用机器学习算法建立了一个建筑环境模型，该模型可用于评估居住者的舒适水平。我们期望所提出的暖通空调控制策略能够为居住者提供始终如一的舒适工作或家庭环境。
