<p>Daylighting has a significant
impact on occupants, including not only visual comfort and visual task
performance but also on workplace satisfaction and psychophysiological
responses such as alertness, mood, and circadian rhythm. Intelligent, dynamic
control of daylight via a building automation system is therefore crucial to
maximizing the positive impacts of daylight provision in perimeter offices.
However, existing daylight-linked controls (DLCs) lacks the fundamental ability
to govern indoor luminous condition in a human-centric manner. It is mainly
because the sensing technologies – such as ceiling-mounted photosensor -
adopted in current DLCs are incapable of monitoring sufficient physical variables
to suit such purpose. Hence, this Thesis aims to utilize a High Dynamic Range
Imaging (HDRI) sensor in DLCs to unlock abilities to enhance human-centric
features that have not been possible with conventional photosensors. The
sensor, made of a low-cost programmable camera
can capture a wide-area luminance distribution highly correlated with occupant
visual perception, compared to conventional illuminance-based metrics. </p>
<p> This Thesis begins with a development of a
window-mounted HDRI sensor for real-time detection of potential glare sources
including the sun. The sensor can capture the full luminance distribution of
the exterior scene visible through the window and identify and locate potential
sources of glare. To overcome the pixel-overflow by the extreme luminance of
the sun and to estimate the accurate 3D position of the glare sources, the HDRI
sensor was upgraded into a new fisheye-stereovision sensor made of dual cameras
with different exposures. Experiments in full-scale offices showed that the calibrated
window-mounted HDRI sensor can efficiently identify and locate potential glare
sources in real time. The daylight control implementation included integration
with shading controls to mitigate the risk of glare and comparison with
conventional shading operation.</p>
<p>Monitoring of indoor luminance
distribution is equally important for human-centric DLCs. There are practical
challenges in utilizing the HDRI sensor for monitoring luminance distribution
perceived from the occupant perspective. Therefore, a new framework was developed for non-intrusive monitoring of
luminance distribution perceived from occupant field-of-view (FOV), using a
fisheye HDRI sensor installed at a non-intrusive position. The framework
leverages the state-of-the-art photogrammetry (Structure-from-Motion –
Multiview Stereo) pipeline to automatically reconstruct 3D surfaces of the
room, which will be used for re-projection of luminance map captured by HDRI sensor
into occupant FOV.</p>
<p>To validate the performance of
the framework, a systematic performance evaluation was conducted in a
real-office experiment under variable lighting conditions to compare the re-projected luminance maps
and the actual luminance measurement captured from occupant positions.</p>
<p> </p>