Flexible Passive Wireless Sensing Platform with Frequency Mapping and Multimodal Fusion

Abstract

As one of the core parts of the Internet-of-things (IOTs), multimodal sensors have exhibited great advantages in fields such as human–machine interaction, electronic skin, and environmental monitoring. However, current multimodal sensors substantially introduce a bloated equipment architecture and a complicated decoupling mechanism. In this work we propose a multimodal fusion sensing platform based on a power-dependent piecewise linear decoupling mechanism, allowing four parameters to be perceived and decoded from the passive wireless single component, which greatly broadens the configurable freedom of a sensor in the IOT. A systematic model is employed to analyze the linear sensing properties and ensure the feasibility of the scheme. The excitation power dependence provides an efficient and quantitative linear decoupling strategy of unidentified combinations for multiple stimuli. As a validation for a wearable device such as electronic skin (e-skin), the functionalized sensing film polyaniline/graphene oxide (PANI/GO) is served to synchronously monitor humidity, temperature, ultraviolet, and proximity through the mapping in resonant frequency (f_s). Compared with the output errors of ∼18.00%, ∼17.50%, ∼15.00%, and ∼20.00%, the maximum experimental errors of temperature, humidity, ultraviolet, and proximity are 5.70%, 4.00%, 5.00%, and 8.30% after decoupling, respectively. In general, the developed single-component multimodal fusion sensing platform offers a strategic advantage for a miniaturization, passive wireless, and inexpensive (less than $1) signal identification system with a facile circuit layout.