Implementation and Analysis of a Capacitive Sensing Network for Intelligent Physically-Integrated Sensing Applications

Abstract

Physically-Integrated (PI) Sensing is a promising new approach for creating sensing systems that have the potential to enhance various perception-based tasks. This enhancement comes from the sensors’ ability to preserve the inherent semantic structure in the data that we extract from the embedded signals.

While PI Sensing itself is not limited to a particular technologies for system implementation, Large-Area Electronics (LAE) – a technology fabric often found in modern display technologies – has proven to be a suitable platform for realizing PI Sensing systems due to its compatibility with large, conformal substrates.

One example of such sensing system is a floor-based capacitive sensing network. While previous work has already demonstrated the deployment of such system at smaller scales and for simpler applications, this thesis is focused on implementing the capacitive sensing network on a larger scale and for human location detection.

This thesis is composed of three main parts: 1) literature review of the relevant technologies, 2) implementation details of the sensing network, and 3) analysis and modeling of the nonidealities associated with the system.