UCLA

ABSTRACT OF THE THESIS

Internet-of-Things

Instructional Platform

for Electrical and Computer Engineering

by

Xu Zhang

Master of Science in Electrical and Computer Engineering

University of California, Los Angeles, 2019

Professor William J. Kaiser, Chair

The motivation of this thesis is to design an interactive and scalable educational platform that delivers latest industrial technology and related electrical and computer engineering fundamentals to engineering students with inspiring and intuitive project examples. Current platform mainly demonstrates merged topics including Internet-of-Things (IoT) network, embedded system, data processing and computing, and machine learning.

The platform is composed of hardware system, software system, and curriculum system. The hardware system is consisted of STMicroelectronics SensorTile kits, STMicroelectronics Nucleo board, and Beaglebone, which provide different levels of IoT hardware components with reasonable costs. The software system is constituted with open-source integrated development environment (IDE), System WorkBench, which is a professional tool to support bare-metal microcontroller programming. The curriculum system has series of tutorials and reference designs, which provide various intuitive projects with detailed instructions and programming guidance.

There are nine tutorials covering fundamental topics including firmware level programming, sensor system signal acquisition, motion sensing, audio sampling and signal processing, Bluetooth low energy (BLE), and inertial sensing. Reference design provides complete, end-to-end experience in development of a system. This experience prepares developers for innovation and implementation of new systems.

This platform is initiated through UCLA Engineering 96C course, which becomes one of the engineering course requirement, and UCLA ECE 180D course, which is the senior capstone design course. UCLA students have collaborated together and developed novel systems for motion classification with SensorTile data sources and machine learning methods developed. Those extraordinary projects are tidily compiled as student project reference designs to inspire other future developments. In addition, the platform is widely adopted by various universities including Columbia University, California State University – North Bridge, Georgia Tech, University of Maine, and so on.