Wireless Sensor and Actuator Networks for Lighting Energy ...

It is obvious from Figure 6-6 and Figure 6-7 that the measured illuminances
differed from the calculated optimal illuminances more significantly towards the north
side of the office (right side) where an artificial wall was placed in the room to simulate
an interior room. The additional absorption and reflection introduced by the virtual wall
might have rendered the illuminance models near the north side of the office less
accurate. Since the illuminance models were generated with respect to an empty room,
the furniture in the real office could have also contributed to the inaccuracies in the
models. Moreover, the lighting hardware, namely the dimming ballasts and fluorescent
lamps, might not guarantee a consistent mapping from the dimming signals to the actual
output luminous due to manufacturing tolerances. These uncertainties signified the need
of sensory feedback for better performances.
6.4.2 Lighting Optimization Algorithm with Sensory Feedback
The sensor information was incorporated for testing the optimal lighting
actuation algorithm with sensory feedback to eliminate possible modeling uncertainties
as well as to respond to daylight. Four occupants were present in the office, and the
photosensors were placed on their desktops to measure the task illuminances and send
the lighting information back for the next iteration of optimization. The algorithm was
set to terminate when the difference between the specified lighting preferences and the
actual illuminances were within five lux for all occupants. As shown in Figure 6-8, it
took four iterations for the light to converge to each occupant’s preference. The top
number of each stack of five numbers represents the preferred lighting specified by each
occupant, and the following four numbers are the sensor readings after the first, second,
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