08.11.2014 Views

Wireless Sensor and Actuator Networks for Lighting Energy ...

Wireless Sensor and Actuator Networks for Lighting Energy ...

Wireless Sensor and Actuator Networks for Lighting Energy ...

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

networks. In addition to the general notion that wireless technologies could significantly<br />

bring down the retrofitting complexity <strong>and</strong> cost, this research explores in depth the ways<br />

in which commercial lighting systems can benefit from wireless sensor <strong>and</strong> actuator<br />

network technologies. This section summarizes the dissertation’s contributions to<br />

theoretical <strong>and</strong> applications-oriented st<strong>and</strong>points.<br />

10.2.1 Theoretical Contributions<br />

The theoretical contributions include the development of sensing <strong>and</strong> actuation<br />

strategies <strong>for</strong> applying wireless network technologies to lighting systems. The<br />

algorithms developed are lightweight <strong>and</strong> capable of being executed in real time on<br />

wireless sensor <strong>and</strong> actuator networks. In addition to office lighting systems, a variety<br />

of sensing <strong>and</strong> actuation applications could potentially benefit from this research.<br />

The mote-FVF sensor validation <strong>and</strong> fusion algorithm is an application of fuzzy<br />

logic that extracts in<strong>for</strong>mation from redundant sensors. The fused in<strong>for</strong>mation is more<br />

valuable than that revealed by every single sensor. The intra-network sensor fusion has<br />

verified the feasibility of in-network data aggregation with the mote-FVF algorithm.<br />

The algorithm fits the massive-deployment nature of wireless sensor networks, <strong>and</strong><br />

addresses the issue of excessive <strong>and</strong> less-reliable sensor readings by condensing<br />

in<strong>for</strong>mation into fewer <strong>and</strong> trustworthy values.<br />

The autonomous sensing with adaptive rate algorithm integrates time series<br />

prediction <strong>and</strong> fuzzy logic so as to dynamically adapt the sensing rate to the change of<br />

stimuli. This algorithm adds another layer of intelligence to the smart sensor nodes by<br />

optimizing the timing <strong>for</strong> both data acquisition <strong>and</strong> the most power-hungry wireless<br />

196

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!