Towards window state detection using image processing in residential and office building facades

窗口(计算) 建筑工程 能量(信号处理) 占用率 图像处理 模拟 计算机科学 实时计算 图像(数学) 计算机视觉 工程类 人工智能 统计 数学 操作系统
作者
David Luong,Russell Richman,Marianne F. Touchie
出处
期刊:Building and Environment [Elsevier BV]
卷期号:207: 108486-108486 被引量:14
标识
DOI:10.1016/j.buildenv.2021.108486
摘要

Although building energy simulation is an essential tool for designers, numerous studies have proven the existence of a performance gap between the estimated and measured energy use. In response, researchers are exploring ways to collect authentic behavioural data to improve existing inaccurate data-driven occupancy behaviour models. An important occupant behaviour currently being studied is window operation behaviour as it results in large consequences on heating/cooling loads and ventilation rates of a building. Ex-situ camera-based window operation monitoring has been proposed as a solution. This study used image processing technologies that automatically identified windows on a façade and determined their individual state (i.e. open, partially open, or closed). The algorithm developed through this study yielded an 89% accuracy rate over all the windows tested. This algorithm was developed to specifically target punched façades with awning windows. Factors that affected the accuracy of ex-situ camera-based window operation monitoring included environmental conditions such as lighting, obstructions, and reflections. Furthermore, there were challenges in determining threshold values used to isolate important image data that defined the window state and location and identifying the significant peaks for window angle image data. The next steps for this research should determine appropriate threshold values that can be used universally through additional testing and to explore new image processing techniques for other window types. • Underdeveloped data-driven occupancy behaviour models contribute to inaccurate simulated energy use. • Ex-situ camera-based system can monitor window behaviour and reduce Hawthorne Effect. • Employed image processing strategies for awning windows on punched facades. • Algorithm produced 90% accurate readings during tests. • Limitations included threshold values and environmental factors during snapshot.
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