ThermoSense: Occupancy Thermal Based Sensing for HVAC Control

Alex Beltran, Varick L. Erickson, Alberto Cerpa
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引用次数: 165

Abstract

In order to achieve sustainability, steps must be taken to reduce energy consumption. In particular, heating, cooling, and ventilation systems, which account for 42% of the energy consumed by US buildings in 2010 [8], must be made more efficient. In this paper, we demonstrate ThermoSense, a new system for estimating occupancy. Using this system we are able to condition rooms based on usage. Rather than fully conditioning empty or partially filled spaces, we can control ventilation based on near real-time estimates of occupancy and temperature using conditioning schedules learned from occupant usage patterns. ThermoSense uses a novel multisensor node that utilizes a low-cost, low-power thermal sensor array along with a passive infrared sensor. By using a novel processing pipeline and sensor fusion, we show that our system is able measure occupancy with a RMSE of only ≈0.35 persons. By conditioning spaces based on occupancy, we show that we can save 25% energy annually while maintaining room temperature effectiveness.
热传感:用于暖通空调控制的占用热传感
为了实现可持续性,必须采取措施减少能源消耗。特别是供热、制冷和通风系统,它们占2010年美国建筑能耗的42%[8],必须提高效率。在本文中,我们演示了一个新的占用率估算系统ThermoSense。使用这个系统,我们可以根据使用情况调整房间。而不是完全调节空的或部分填充的空间,我们可以根据占用率和温度的近实时估计来控制通风,使用从占用者使用模式中学习的调节时间表。ThermoSense采用了一种新型的多传感器节点,该节点利用了低成本、低功耗的热传感器阵列以及被动红外传感器。通过使用新的处理流程和传感器融合,我们表明我们的系统能够以仅≈0.35人的RMSE测量占用率。通过根据占用情况调节空间,我们可以在保持室温有效性的同时每年节省25%的能源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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