Wireless Sensor and Actuator Networks for Lighting Energy ...

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B.7 Human Subject Test Questionnaire...........................................................251 B.8 Human Subject Test Interview Script .......................................................255 Appendix C Cost Analysis .................................................................................256 C.1 Average Illuminance Calculation Sheet....................................................256 C.2 Example of System Payback Period Calculation.......................................258 viii
List of Figures Figure 1-1 Research system architecture........................................................................3 Figure 2-1 Primary energy consumption in commerical buildings. ..............................15 Figure 2-2 Primary energy expenditure in commercial buildings. ................................15 Figure 2-3 Energy consumption in commercial sector. ................................................16 Figure 2-4 Energy usage in office buildings.................................................................16 Figure 2-5 Wireless sensor platforms and sensor boards..............................................22 Figure 4-1 Mote-FVF algorithm architecture...............................................................48 Figure 4-2 Gaussian correlation curve. ........................................................................50 Figure 4-3 Membership functions for defining the center of validation curve...............52 Figure 4-4 Fuzzy centered validation curve. ................................................................52 Figure 4-5 Membership functions for determining the adaptive parameter . ..............54 Figure 4-6 Mote-FVF with median value majority voting scheme. ..............................58 Figure 4-7 Mote-FVF with Gaussian correlation majority voting scheme. ...................58 Figure 4-8 Comparison of variations of sensor validation and fusion algorithm...........60 Figure 5-1 Mechanism for adaptive sampling [92].......................................................63 Figure 5-2 Architecture of adaptive sensing rate algorithm..........................................63 Figure 5-3 Prediction performance of Kalman filtering................................................66 Figure 5-4 Adaptive Wiener filter................................................................................66 Figure 5-5 Prediction performance of adaptive Wiener filtering...................................68 Figure 5-6 Prediction performance of double exponential smoothing...........................69 Figure 5-7 Membership functions for determining sensing rate....................................71 ix
Page 1 and 2: Wireless Sensor and Actuator Networ
Page 3 and 4: Abstract Wireless Sensor and Actuat
Page 5 and 6: To my wife for having faith in me a
Page 7 and 8: Table of Contents Chapter 1 Introdu
Page 9 and 10: 6.4.2 Lighting Optimization Algorit
Page 11: 10.2.1 Theoretical Contributions...
Page 15 and 16: Figure 7-8 Voltage divider. .......
Page 17 and 18: Figure 9-31 Energy savings vs. payb
Page 19 and 20: The integration of wireless sensor
Page 21 and 22: esulting lighting is optimal in the
Page 23 and 24: acquisition and wireless transmissi
Page 25 and 26: a central base computer for sensor
Page 27 and 28: optimal light settings were in turn
Page 29 and 30: possibility of wireless actuator ne
Page 31 and 32: Chapter 2 Motivation The motivation
Page 33 and 34: [21]. Lighting accounts for 30% of
Page 35 and 36: Table 2-1 summarizes each of the co
Page 37 and 38: from light level tuning impossible
Page 39 and 40: used in the progress of this resear
Page 41 and 42: 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
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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
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Figure 4-8 Comparison of variations
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The daylighting system application
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The key components are the predicti
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Figure 5-3 Prediction performance o
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Figure 5-5 Prediction performance o
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Among them, adaptive Wiener filteri
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even though the sensed environment
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5.3 Simulation and Experiment Resul
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Figure 5-11 Adaptive sensing with d
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Figure 5-13 Damped adaptive sensing
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Chapter 6 Optimal Lighting Actuatio
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of the workplane level illuminance
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office with K luminaires, for examp
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E sub = e pq e rs e xy 1
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optimizer for a consistency check.
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Figure 6-4 Pseudo code of the light
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simulation was to show that the opt
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It is obvious from Figure 6-6 and F
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Chapter 7 Wireless-Enabled Lighting
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determined to be 0-2000 lux. Conseq
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discrete outputs from the motes spa
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actuation technologies, and additio
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Figure 7-8 Voltage divider. Since t
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Given the 256-level dimming capabil
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Figure 7-11 Prototyping Luminaire S
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to its simplicity. Although coded w
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The second experiment was executed
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Chapter 8 System Verification on Hu
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commercial system was randomized fo
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8.2.1 Hardware Implementation in Sm
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eference point on the desktop was s
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commands were received. In addition
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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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