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will broaden the application to different types of commercial or even residential buildings. Delivering satisfying task illuminances by properly actuating the electric lights is a critical aspect of creating quality lighting. On the other hand, glare, excessive natural light, and heat caused by direct sunlight are also factors that may jeopardize lighting quality and comfort and should not be overlooked. Blinds and windows with special treatment, such as electrochromatic windows, are mechanisms mostly used for manually blocking out undesired extraneous light. Inappropriate use of the lightblocking systems not only compromises lighting comfort but also sacrifices energy savings. The actuation capability of the wireless sensor and actuator networks provides a promising solution for integrating blind and window control into automatic lighting systems. Advanced control strategies need to be developed to coordinate the control of both the electric lights and the blinds/windows for maximum lighting quality as well as energy savings. 10.3.3 Integration with Other Lighting Energy Management Strategies As pointed out in Chapter 2.1.2, maximum savings will occur with a proper combination of effective energy management strategies. The current research system integrates daylight harvesting and light level tuning. While daylight harvesting possesses the highest savings potential for open-plane offices receiving significant daylight, other strategies, such as occupancy sensing discussed in the previous section, will also help cut down the energy usage. 201
Demand response, which temporarily reduces energy consumption during peak demand hours, is currently the most discussed energy management strategy for preventing blackout or brownout. Although not aimed at generating significant energy savings, demand response is the key technology with which modern energy-efficient systems must be equipped or at least compatible. For lighting systems, load shedding translates to reducing the light below the original setting by certain amounts. Given occupants’ lighting preferences, preferably well-modeled ones as discussed in Chapter 10.3.1, it would be interesting to incorporate load shedding into the research system for delivering the light that least compromises the users’ preferences during the peak hours. 10.3.4 Integration with the Building Management System It has become increasingly common for large-scale buildings to employ building management systems (BMS) to coordinate the mechanical and electrical systems and manage energy usage. Being the largest electricity consumer among all the electrical systems in buildings as pointed out in Chapter 2.1.1, it is crucial to integrate the lighting system into building management systems. This dissertation research has focused on the energy efficiency of building lighting systems alone; however, energy usage of all the electrical and even mechanical systems of a building may be interrelated in reality. For instance, the room temperature could rise due to the incoming heat from the windows while harvesting daylight, and consequently the air conditioning system has to compensate for it to ensure a comfortable environment. As a result, some of the energy saved from the lighting 202
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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
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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
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
Page 178 and 179: 9.4 Daylight Response The second ph
Page 180 and 181: Furthermore, the structure allows t
Page 182 and 183: Figure 9-16 Daylight harvesting tes
Page 184 and 185: Figure 9-18 Sensor readings in the
Page 186 and 187: then gradually dimmed. After reachi
Page 190 and 191: Seven-occupant case with simulated
Page 194 and 195: under significant daylight. Again,
Page 196 and 197: newly calculated light settings may
Page 198 and 199: Annual energy consumption = ( Numbe
Page 200 and 201: Figure 9-30 Energy savings vs. payb
Page 202 and 203: have partially contributed to the h
Page 204 and 205: $40 per unit and the system achieve
Page 206 and 207: performance of the current research
Page 208 and 209: sensors. The research in [14] prese
Page 210 and 211: Other than optimizing the energy co
Page 212 and 213: lighting configuration in the offic
Page 214 and 215: communications. The adaptive sensin
Page 216 and 217: integration of the research system
Page 220 and 221: system could be reallocated to oper
Page 222 and 223: entities could be tremendously crit
Page 224 and 225: [7] J. A. Veitch and G. R. Newsham,
Page 226 and 227: [20] K. A. Karmel, High Performance
Page 228 and 229: [34] P. Levis, S. Madden, J. Polast
Page 230 and 231: International Workshop on Wireless
Page 232 and 233: [57] LonMark International, "Fact S
Page 234 and 235: [71] S. Sahni and X. Xu, "Algorithm
Page 236 and 237: Proceedings of the 1st Internationa
Page 238 and 239: [99] SPOT: Sensor Placement + Optim
Page 240 and 241: [113] Advance Transformer Technical
Page 242 and 243: A.2 Circuit Schematics of Photosens
Page 244 and 245: A.4 Circuit Schematics of the Secon
Page 246 and 247: Appendix B Human Subject Test B.1 C
Page 248 and 249: (a) Sensor placement of subject No.
Page 250 and 251: B.2 Comparison of System Performanc
Page 252 and 253: B.3 Summary of the Responses from t
Page 254 and 255: B.4 Human Subject Test Approval Let
Page 256 and 257: B.5 Human Subject Test Protocol Nar
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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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