Publication Date

Fall 2020

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Teng Moh

Second Advisor

Melody Moh

Third Advisor

Brad Hoffert

Keywords

Lidar, AI, Smart Cities

Abstract

As governments and private companies alike race to achieve the vision of a smart city — where artificial intelligence (AI) technology is used to enable self-driving cars, cashier-less shopping experiences and connected home devices from thermostats to robot vacuum cleaners — advancements are being made in both software and hardware to enable increasingly real-time, accurate inference at the edge. One hardware solution adopted for this purpose is the LiDAR sensor, which utilizes infrared lasers to accurately detect and map its surroundings in 3D. On the software side, developers have turned to artificial neural networks to make predictions and recommendations with high accuracy. These neural networks have the potential, particularly run on purpose-built hardware such as GPUs and TPUs, to make inferences in near real-time, allowing the AI models to serve as a usable interface for real-world interactions with other AI-powered devices, or with human users. This paper aims to example the joint use of LiDAR sensors and AI to understand its importance in smart city environments.

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