Wireless Sensor and Actuator Networks for Lighting Energy ...

Figure 5-11 Adaptive sensing with double exponential smoothing predictive model.
A close examination of the adaptation of the sensing interval in plot (b) of
Figure 5-9 to Figure 5-11 reveals that the sensing rate changed quite randomly. There is
no clear correlation between two consecutive sensing intervals. The sensing rate can be
very high in one instance, but determined to be very low in the following instance. For
example, around the 157 th minute in Figure 5-10(b), the sampling interval was adapted
to 450 seconds/sample although the previous ones were much lower. This caused
undesirable loss of information as seen in Figure 5-10(a) – the gap between the solid
blue line and the dashed green line reflects the fact that the adapted sensing interval
failed to capture the daylight change in the blue valley.
Figure 5-12, Figure 5-13, and Figure 5-14 show the performance of the damped
sensing rate adaptor with Kalman filtering, adaptive Wiener filtering, and the double
exponential smoothing model respectively. Like the figures for the undamped version,
the solid blue line in (a) of each figure is the daylight data sampled uniformly at 10
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