We inhabit space. This means our deepest mental and emotional understanding of the world is tied intimately to our experiences as we perceive them in a physical context. Just like a book or film may induce a sense of presence, so too may our modern sensor drenched infrastructures and mobile information spaces. With the recent development of personal and ubiquitous computing devices that we always carry with us, and increased connectivity and robustness of wireless connections, there is an increasing tie between people and things around them. This also includes the space people inhabit. However, such enhanced experiences are usually limited to a personal environment with a personal smartphone being the central device. We would like to bring such technology enhanced experiences to large public spaces with many occupants where their movement patterns, and interactions can be shared, recorded, and studied in order to improve the occupants' efficiency and satisfaction. Specifically, we use sensor networks and ubiquitous computing to create smart built environments that are seamlessly aware of and responsive to the occupants. Human sensing system is one of the key enabling technologies for smart built environments. We present our research findings related to the design and deployment of an indoor human sensing system in large public built spaces. We use a case study to illustrate the challenges, opportunities, and lessons for the emerging field of human building interaction. We present several fundamental design trade-offs, applications, and performance measures for the case study. / Master of Science / The recent advances in mobile technologies, like smart phones and enhanced wireless communication, allow people to experience added comfort and convenience brought by these devices. For example, smart lighting and air conditioning control can be set remotely, before people arrive at their homes. However, these personal experiences are usually limited to personal spaces and tied to a specific personal smart phone. When it comes to public spaces, we seldom see such technological advancement being utilized. In reality, the concept of smart public spaces is still limited to technologies like opening / closing a door automatically. We discuss the reasons that cause such difference between personal and public spaces. We argue that Human Building Interactions should be shaped around non-intrusive indoor human sensing technologies. We present discussions, considerations and implementation of a system that uses a low cost camera network for indoor human sensing. We also describe several applications based on the developed system. We demonstrate how to bring technology enhanced experiences to public built spaces and provide smart built environments.

The capability to detect, track and monitor human activities behind building walls and other non-line-of-sight environments is an important component of security and surveillance operations. Over the years, both ultrawideband and Doppler based radar techniques have been researched and developed for tracking humans behind walls. In particular, Doppler radars capture some interesting features of the human radar returns called microDopplers that arise from the dynamic movements of the different body parts. All the current research efforts have focused on building hardware sensors with very specific capabilities. This dissertation focuses on developing a physics based Doppler radar simulator to generate the dynamic signatures of complex human motions in nonline-of-sight environments. The simulation model incorporates dynamic human motion, electromagnetic scattering mechanisms, channel propagation effects and radar sensor parameters. Detailed, feature-by-feature analyses of the resulting radar signatures are carried out to enhance our fundamental understanding of human sensing using radar. First, a methodology for simulating the radar returns from complex human motions in free space is presented. For this purpose, computer animation data from motion capture technologies are exploited to describe the human movements. Next, a fast, simple, primitive-based electromagnetic model is used to simulate the human body. The microDopplers of several human motions such as walking, running, crawling and jumping are generated by integrating the animation models of humans with the electromagnetic model of the human body. Next, a methodology for generating the microDoppler radar signatures of humans moving behind walls is presented. This involves combining wall propagation functions derived from the finite-difference time-domain (FDTD) simulation with the free space radar simulations of humans. The resulting hybrid simulator of the human and wall is used to investigate the effects of both homogeneous and inhomogeneous walls on human microDopplers. The results are further corroborated by basic point-scatterer analysis of different wall effects. The wall studies are followed by an analysis of the effects of flat grounds on human radar signatures. The ground effect is modeled using the method of images and a ground reflection coefficient. A suitable Doppler radar testbed is developed in the laboratory for simulation validation. Measured data of different human activities are collected in both line-of-sight and through-wall environments and the resulting microDoppler signatures are compared with the simulation results. The human microDopplers are best observed in the joint timefrequency space. Hence, suitable joint time-frequency transforms are investigated for improving the display and the readability of both simulated and measured spectrograms. Finally, two new Doppler radar paradigms are considered. First, a scenario is considered where multiple, spatially distributed Doppler radars are used to measure the microDopplers of a moving human from different viewing angles. The possibility of using these microDoppler data for estimating the positions of different point scatterers on the human body is investigated. Second, a scenario is considered where multiple Doppler radars are collocated in a two-dimensional (2-D) array configuration. The possibility of generating frontal images of human movements using joint Doppler and 2-D spatial beamforming is considered. The performance of this concept is compared with that of conventional 2-D array processing without Doppler processing. / text