Abstract

Whispering-gallery-mode (WGM) optical resonators in which light is confined by total internal reflection have found broad applications ranging from optical communications, microlasers, sensing, opto-mechanics to quantum optics. However, overcoming obstacles of practical applications for WGM resonators is absolutely a big challenge. First, we report the first realization of a compact WGM sensing system, which integrates a tunable laser, a current source, a temperature controller, a function generator, an oscilloscope, a photodiode detector, a testing computer with customized testing software, and a packaged WGM sensor into a phone-sized embedded system. Second, we deploy the WGM sensor in the Internet of things (IoT) sensor network. We demonstrate a WGM sensor based embedded IoT device. By connecting the Wi-Fi unit to the internet, a worldwide, real-time control of this system can be realized. We also conducted the aerial thermal mapping experiment by using this wireless sensing system. Third, we report a sensing model with high noise immunity using machine learning algorithm for WGM mode shift sensing. Furthermore, an artificial intelligence at the edge embedded device is designed for real-time inference of sensing results which is running the pre-trained neural network model. This platform is also integrated with a customized iOS application for system control and sensing result display via Wi-Fi antenna. Our algorithm and platform not only exhibit high noise immunity characteristics, but also potential flexibility in configuration for different sensing applications.

Committee Chair

LAN YANG

Committee Members

Ulugbek Kamilov, Chuan Wang, Xuan Zhang, Shen Zeng,

Comments

Permanent URL: https://doi.org/10.7936/zwxm-e933

Degree

Doctor of Philosophy (PhD)

Author's Department

Electrical & Systems Engineering

Author's School

McKelvey School of Engineering

Document Type

Dissertation

Date of Award

Winter 12-15-2019

Language

English (en)

Author's ORCID

http://orcid.org/0000-0003-2678-124X

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Available for download on Friday, December 15, 2119

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Engineering Commons

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