Wireless Sensor and Actuator Networks for Lighting Energy ...

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seconds/sample, and the dashed green line is the daylight information reconstructed from the adaptively sampled data. Compared to the original 1851 samples, 236, 227, and 358 data points were sampled with respect to each predictive model during the entire sensing task. In other words, only less than one-fifth of the sensing effort was required to pertinently represent daylight change in that period. Plot (b) of each figure details how the sensing rates were adapted over time. Figure 5-12 Damped adaptive sensing with Kalman filtering predictive model. 77
Figure 5-13 Damped adaptive sensing with Wiener filtering predictive model. Figure 5-14 Damped adaptive sensing with double exponential smoothing predictive model. At the cost of more samples due to the additional damping, each adaptive sensing task resulted in even better fidelity in capturing the daylighting information than its undamped counterpart. In plot (b) of Figure 5-12 to Figure 5-14, it is obvious that the 78
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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
Page 43 and 44: office, and industrial applications
Page 45 and 46: Chapter 3 Related Research and Lite
Page 47 and 48: Although radio frequency is a suppo
Page 49 and 50: channels with different capabilitie
Page 51 and 52: In practice, fusion of sensor data
Page 53 and 54: The emergence of wireless sensor ne
Page 55 and 56: A is empty f A (x) = 0, x X (3.1)
Page 57 and 58: Convex combination: the relation Th
Page 59 and 60: where no crisp boundary can be defi
Page 61 and 62: developed by Dantzig [87]. The ineq
Page 63 and 64: sensor network is far more valuable
Page 65 and 66: Figure 4-1 Mote-FVF algorithm archi
Page 67 and 68: Figure 4-2 Gaussian correlation cur
Page 69 and 70: predicted reading. Note that the of
Page 71 and 72: fuzzification and m for the defuzz
Page 73 and 74: mote sensors were arranged in a 3-b
Page 75 and 76: 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: Figure 5-11 Adaptive sensing with d
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 128 and 129: to its simplicity. Although coded w
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
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(a) Figure 8-6 Sensor placement of
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lower meter readings was that the m
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(2) Subtle and invisible shadows ma
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function keys are. The function key
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deliberately perturbed the lights d
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Table 8-2 Summary of the test on pr
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Current Level on the investigator
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Chapter 9 System Implementation and
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Figure 9-1 Floor plan of the small
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Figure 9-3 System operation diagram
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campus-wide lighting maintenance, w
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message is addressed. The destinati
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Both the actuation and the grouping
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The construction or updating of the
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determines if this message is for u
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Figure 9-12 Lighting preset setting
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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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243
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245
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247
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249
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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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