Wireless Sensor and Actuator Networks for Lighting Energy ...

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corresponding ancillary circuitry amplifies the signal from the photosensitive element to match the input range of the analog-to-digital converter (ADC) on the mote platform. The Hamamatsu S7686 silicon photodiode was selected as the photosensitive element. This specific photodiode possesses sensitivity close to that of human eyes and is color-corrected to match the CIE curve. The CIE curve is a color model based on human perception that was developed by the Commission Internationale de l’Eclairage (the International Commission on Illumination) committee. The spectral response of the photodiode is reproduced in Figure 7-1, in which the CIE curve is overlaid. Figure 7-1 Spectral response of Hamamatsu 7686 photodiode [101]. Since the wireless photosensors are meant for being deployed on desktops to measure workplane illuminance, the normal operating range of the photosensor is 97
determined to be 0-2000 lux. Consequently, the supporting circuitry was designed to translate the electronic signal produced by the photodiode in the normal operating range to span the full voltage range of the mote ADC input. The resulting photosensor boards integrated with different mote platforms are shown in Figure 2-5, and the electronic circuit schematics can be found in Appendix A.1 and A.2. Except for the spectral response, the behaviors of the wireless mote photosensors, including the sensor reading acquisition rate, data processing, the communication and networking scheme, etc., are defined in the operating system of the mote. Figure 7-2 illustrates the calibration curve of one of the photosensor boards. The sensor board was calibrated against a high fidelity light meter. Although the operating range of the photosensor was set to 0-2000 lux, the controlled lighting used in this calibration can only provide at most 1000 lux on the test surface. The illuminance was increased from 0 to 1000 lux with a 50 lux interval, and the digital reading from the ADC on the mote platform was recorded. The blue dots show the data points of the illuminances versus the ADC output readings, and the red line is a first-order polynomial fitting. The plot confirms that the response of the photosensor is linear. 98
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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
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 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: Chapter 7 Wireless-Enabled Lighting
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
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
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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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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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