Wall++: Room-Scale Interactive and Context-Aware Sensing

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Human Pose & Activity RecognitionContext-Aware ComputingUbiquitous Computing

Human environments are typified by walls – homes, offices, restaurants, schools, museums and pretty much every indoor context one can imagine. In many cases, they make up a majority of readily accessible indoor surface area, and yet they are static – their primary function is to be a wall, separating spaces and hiding infrastructure. We present Wall++, a low-cost sensing approach that allows walls to become a smart infrastructure. Instead of merely separating spaces, walls can now enhance rooms with sensing, interactivity and computation. Our wall treatment and sensing hardware can track users’ touch and gestures, as well as estimate body pose if they are close. By capturing airborne electromagnetic noise, we can also recognize what appliances are active and where they are located, and track and identify signal-emitting tags carried by users. Through a series of evaluations, we demonstrate Wall++ can enable robust room-scale interactive and context sensing applications.

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https://hci.top/en/papers/chi/4316/2018

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CHI
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Year
2018
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5 authors
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Human Pose & Activity Recognition, Context-Aware Computing, Ubiquitous Computing
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