Smart Environments with Wide-Area Sensors

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

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

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

activity sensing technology. 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.