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to its simplicity. Although coded with a different language, the integrity of the mote- FVF algorithm remained intact. The prototyping luminaire structure was equipped with the mote-based ballast actuation module so as to dim the lights wirelessly. Furthermore, the experiment system was made into a self-contained illuminance regulation system that maintained the illuminance on the testbed at a specified value without the presence of a central computer to coordinate the control actions. The mote integrated with the actuation module was embedded with a simple rule-based control law, and it listened to the fused readings from the cluster of mote sensors. Upon receiving a fused value from the sensor cluster, the actuation mote calculated and performed the control action based on the control law in order to maintain the testbed illuminance at the setpoint. Although no extraneous computer was required in the experiment system, a computer was still employed to intercept the readings from each sensor and the fused values for data gathering purpose. The default setpoint of 500 lux was hard-coded in the actuation mote, which could be changed in real-time by sending a management command to the actuation module specifying a new setpoint from the computer. Experiment results The first experiment lasted over 17 hours to show that the system can sustain long-term unattended operations. The luminaire structure was located in a research lab without windows to introduce natural daylight perturbation. In order to evaluate the system’s ability to regulate the desktop illuminance at the setpoint, the overhead 111
luminaires were used to simulate extraneous lighting. The setpoint of this experiment was specified at 550 lux at all times. Figure 7-12(a) shows the fused values (blue solid line) and the readings from one of the mote sensors (magenta dashed line) gathered at the computer. For clarity and readability, the raw data from the other five sensors are omitted in this plot. The big spikes indicate the times when the overhead lights were turned on or off and the overall illuminance on the desktop was rapidly brought back to 550 lux. Due to the large number of data points squeezed into the plot, the fused line in Figure 7-12(a) seems thick and fluctuates significantly. Figure 7-12(b) focuses on the fused value from the first half hour of Figure 7-12(a) to show the performance of the system with better resolution. The desktop illuminance was regulated within 5% of the setpoint during the entire experiment. The magenta dashed line, which is based on the raw readings from sensor No.3, stopped around the fourth hour because the mote ran out of batteries. The fact that the blue line, the fused values, was not affected by the malfunctioning sensor verified the robustness of the mote-FVF algorithm under sensor failure. (a) (b) Figure 7-12 Long term desktop illuminance regulation. 112
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Wireless Sensor and Actuator Networ
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Abstract Wireless Sensor and Actuat
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To my wife for having faith in me a
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Table of Contents Chapter 1 Introdu
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6.4.2 Lighting Optimization Algorit
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10.2.1 Theoretical Contributions...
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List of Figures Figure 1-1 Research
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Figure 7-8 Voltage divider. .......
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Figure 9-31 Energy savings vs. payb
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The integration of wireless sensor
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esulting lighting is optimal in the
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acquisition and wireless transmissi
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a central base computer for sensor
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optimal light settings were in turn
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possibility of wireless actuator ne
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Chapter 2 Motivation The motivation
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[21]. Lighting accounts for 30% of
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Table 2-1 summarizes each of the co
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from light level tuning impossible
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used in the progress of this resear
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are expected to autonomously config
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office, and industrial applications
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Chapter 3 Related Research and Lite
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Although radio frequency is a suppo
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channels with different capabilitie
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In practice, fusion of sensor data
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The emergence of wireless sensor ne
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A is empty f A (x) = 0, x X (3.1)
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Convex combination: the relation Th
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where no crisp boundary can be defi
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developed by Dantzig [87]. The ineq
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sensor network is far more valuable
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Figure 4-1 Mote-FVF algorithm archi
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Figure 4-2 Gaussian correlation cur
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predicted reading. Note that the of
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fuzzification and m for the defuzz
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mote sensors were arranged in a 3-b
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Figure 4-6 Mote-FVF with median val
Page 77 and 78: Figure 4-8 Comparison of variations
Page 79 and 80: The daylighting system application
Page 81 and 82: The key components are the predicti
Page 83 and 84: Figure 5-3 Prediction performance o
Page 85 and 86: Figure 5-5 Prediction performance o
Page 87 and 88: Among them, adaptive Wiener filteri
Page 89 and 90: even though the sensed environment
Page 91 and 92: 5.3 Simulation and Experiment Resul
Page 93 and 94: Figure 5-11 Adaptive sensing with d
Page 95 and 96: Figure 5-13 Damped adaptive sensing
Page 97 and 98: Chapter 6 Optimal Lighting Actuatio
Page 99 and 100: of the workplane level illuminance
Page 101 and 102: office with K luminaires, for examp
Page 103 and 104: E sub = e pq e rs e xy 1
Page 105 and 106: optimizer for a consistency check.
Page 107 and 108: Figure 6-4 Pseudo code of the light
Page 109 and 110: simulation was to show that the opt
Page 111 and 112: It is obvious from Figure 6-6 and F
Page 113 and 114: Chapter 7 Wireless-Enabled Lighting
Page 115 and 116: determined to be 0-2000 lux. Conseq
Page 117 and 118: discrete outputs from the motes spa
Page 119 and 120: actuation technologies, and additio
Page 122 and 123: Figure 7-8 Voltage divider. Since t
Page 124 and 125: Given the 256-level dimming capabil
Page 126 and 127: Figure 7-11 Prototyping Luminaire S
Page 130 and 131: The second experiment was executed
Page 132 and 133: Chapter 8 System Verification on Hu
Page 134 and 135: commercial system was randomized fo
Page 136 and 137: 8.2.1 Hardware Implementation in Sm
Page 138 and 139: eference point on the desktop was s
Page 140 and 141: commands were received. In addition
Page 142 and 143: were provided with three wireless p
Page 144 and 145: (a) Figure 8-6 Sensor placement of
Page 146 and 147: lower meter readings was that the m
Page 148 and 149: (2) Subtle and invisible shadows ma
Page 150 and 151: function keys are. The function key
Page 152 and 153: deliberately perturbed the lights d
Page 154 and 155: Table 8-2 Summary of the test on pr
Page 156 and 157: Current Level on the investigator
Page 158 and 159: Chapter 9 System Implementation and
Page 160 and 161: Figure 9-1 Floor plan of the small
Page 162 and 163: Figure 9-3 System operation diagram
Page 164 and 165: campus-wide lighting maintenance, w
Page 166 and 167: message is addressed. The destinati
Page 168 and 169: Both the actuation and the grouping
Page 170 and 171: The construction or updating of the
Page 172 and 173: determines if this message is for u
Page 174 and 175: Figure 9-12 Lighting preset setting
Page 176 and 177: Figure 9-13 Average hourly percent
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9.4 Daylight Response The second ph
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Furthermore, the structure allows t
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Figure 9-16 Daylight harvesting tes
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Figure 9-18 Sensor readings in the
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then gradually dimmed. After reachi
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Seven-occupant case with simulated
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under significant daylight. Again,
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newly calculated light settings may
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Annual energy consumption = ( Numbe
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Figure 9-30 Energy savings vs. payb
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have partially contributed to the h
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$40 per unit and the system achieve
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performance of the current research
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sensors. The research in [14] prese
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Other than optimizing the energy co
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lighting configuration in the offic
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communications. The adaptive sensin
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integration of the research system
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will broaden the application to dif
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system could be reallocated to oper
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entities could be tremendously crit
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[7] J. A. Veitch and G. R. Newsham,
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[20] K. A. Karmel, High Performance
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[34] P. Levis, S. Madden, J. Polast
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International Workshop on Wireless
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[57] LonMark International, "Fact S
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[71] S. Sahni and X. Xu, "Algorithm
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Proceedings of the 1st Internationa
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[99] SPOT: Sensor Placement + Optim
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[113] Advance Transformer Technical
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A.2 Circuit Schematics of Photosens
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A.4 Circuit Schematics of the Secon
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Appendix B Human Subject Test B.1 C
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(a) Sensor placement of subject No.
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B.2 Comparison of System Performanc
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B.3 Summary of the Responses from t
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B.4 Human Subject Test Approval Let
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B.5 Human Subject Test Protocol Nar
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241
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245
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B.7 Human Subject Test Questionnair
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253
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B.8 Human Subject Test Interview Sc
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Luminaire surface depreciation: 1.0
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Table C-1 Daylight reception durati
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At the rate of 9.62 cents per kWh a
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