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Project Introduction

This proposal aims to build Smart Buttons, a bio-enabled wearable device weighing less than 2 grams. Instead of building yet-another miniaturized wearable device, a transformative architecture is created where the designconstraints (e.g., form factor, cost and energy) make it critically necessary to leverage bio-enabled functions to achieve a feasible design. Specifically, a network of smart buttons will be built that scales from a few buttons for each person individually to over a hundred of buttons for a crowd. This network simultaneously records, generates, compiles posture and interaction data spanning various scenarios, time scales and physical settings. The smart button platform will be able to assist domain scientists in understanding human posture and behavior as well as social interaction in a crowd.

              

Intellectual Merit

The intellectual contributions and the deliverables of this proposed work are manifested by a novel bio-enable design philosophy and a set of concrete approaches to seamlessly integrate computation with bio-enabled functions. Despite the fact that a few systems have demonstrated how to effectively monitor behaviors, none of them attempts to utilize bio-enabled functions to build wearable devices. The point of departure from the state-ofthe-art is that subjects (e.g., human) are treated not only as the source of information, but also as the source of functionality. This is indeed an underexploited territory with many challenging issues. For example, unlike electronic computation functions, bio-enabled functions are highly unpredictable and have inherent uncertainty in both measurement and control. Modeling bio-enabled functions and their related uncertainty in terms of measurement and control is largely unknown. Furthermore, it is necessary to discover (i) how computation from electronic systems interact with physical bio-enabled functions from living subjects, and (ii) how to integrate these functions. The proposal work first demonstrates a few cases of bio-enabled functions and their effectiveness, including bio-enabled proximity detection, ranging, bio-enabled on-demand sensing, bio-enabled networking and energy management. After these case studies, reusable patterns are extracted, and principles and methodologies to design bio-enabled wearable devices are derived. The results can be used in the future by domain scientists to support (i) individual’s behavior predictions and generalizations, and (ii) crowd social interaction modeling and control.

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