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   CMU-HCII-20-111 Human-Computer Interaction Institute School of Computer Science, Carnegie Mellon University 
 
 Smart Environments with Wide-Area Sensors Yang Zhang Novmeber 2020 Ph.D. Thesis 
 
 In this dissertation work, I identify the critical challenges faced in current activity sensing and propose a new direction for tackling these challenges. Specifically, instead of deploying many sensors throughout user environments, I propose a new sensing technique that involves the use of fewer but more powerful sensors than the existing methods. I call these sensors wide-area sensors. I built five systems based on capacitive sensing, radio frequency sensing, energy harvesting, and laser vibrometry. These systems achieve room-, building- and city-scale sensing by adapting everyday objects for sensing using low-cost instrumentation in concert with signals that can travel long distances. Additionally, I have conducted a series of background investigations and system performance evaluations to prove that such wide-area sensing systems can be low-cost, low-maintenance, and general-purpose while being able to sense rich signals. Finally, I summarize the contribution of this thesis and propose several future research efforts. 
140 pages  
 
Jodi Forlizzi, Head, Human-Computer Interaction Institute 
 
 
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