Smart Environments with Wide-Area Sensors

<div>We live in an era where computer applications are no longer constrained by the proximity of big and expensive computers, and can extend to larger common spaces</div><div>due to the ubiquity of sensors, electronics, and their ever-decreasing sizes and costs. This computing evolution has fueled the emerging concept of smart environments</div><div>with applications such as context-aware computing, building and personal informatics, mental and physical health monitoring, and accessibility for the elderly and handicapped. However, smart environments are only as smart as what they can sense – the key to realizing this future is the development of accurate, reliable, and versatile</div><div>activity sensing technology. In this dissertation work, I identify the critical challenges faced in current activity</div><div>sensing and propose a new direction for tackling these challenges. Specifically, instead of deploying many sensors throughout user environments, I propose a new</div><div>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</div><div>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</div><div>sense rich signals. Finally, I summarize the contribution of this thesis and propose several future research efforts.</div>