Artificial intelligence monitoring at the edge for smart nation deployment

Machine learning and computer vision have become closely related in the recent years. With the vast amount of data generated in this heavily digitalized century, the advancement of machine learning field is growing exponentially. The ability to utilize data to categories and predict pattern made mac...

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Main Author: Lim, Shi Yong
Other Authors: Gan Woon Seng
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141069
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1410692023-07-07T18:41:23Z Artificial intelligence monitoring at the edge for smart nation deployment Lim, Shi Yong Gan Woon Seng School of Electrical and Electronic Engineering Smart Nation TRANS Lab EWSGAN@ntu.edu.sg Engineering::Electrical and electronic engineering Machine learning and computer vision have become closely related in the recent years. With the vast amount of data generated in this heavily digitalized century, the advancement of machine learning field is growing exponentially. The ability to utilize data to categories and predict pattern made machine learning a powerful tool to solve problems in many fields. In the field of computer vision, machine learning helps to improve recognition and tracking. In this paper, we will discuss the possibility of using machine learning technique to implement Direction of Arrival (DOA) estimation in embedded system to detect the source of audio signal. This project consists of mainly two parts, data acquisition and creating machine learning model for estimation. The performance is evaluated with the accuracy outcome of the model to estimate the angel of audio played in the environment. Bachelor of Engineering (Information Engineering and Media) 2020-06-04T00:16:25Z 2020-06-04T00:16:25Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141069 en A3092-91 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Lim, Shi Yong
Artificial intelligence monitoring at the edge for smart nation deployment
description Machine learning and computer vision have become closely related in the recent years. With the vast amount of data generated in this heavily digitalized century, the advancement of machine learning field is growing exponentially. The ability to utilize data to categories and predict pattern made machine learning a powerful tool to solve problems in many fields. In the field of computer vision, machine learning helps to improve recognition and tracking. In this paper, we will discuss the possibility of using machine learning technique to implement Direction of Arrival (DOA) estimation in embedded system to detect the source of audio signal. This project consists of mainly two parts, data acquisition and creating machine learning model for estimation. The performance is evaluated with the accuracy outcome of the model to estimate the angel of audio played in the environment.
author2 Gan Woon Seng
author_facet Gan Woon Seng
Lim, Shi Yong
format Final Year Project
author Lim, Shi Yong
author_sort Lim, Shi Yong
title Artificial intelligence monitoring at the edge for smart nation deployment
title_short Artificial intelligence monitoring at the edge for smart nation deployment
title_full Artificial intelligence monitoring at the edge for smart nation deployment
title_fullStr Artificial intelligence monitoring at the edge for smart nation deployment
title_full_unstemmed Artificial intelligence monitoring at the edge for smart nation deployment
title_sort artificial intelligence monitoring at the edge for smart nation deployment
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/141069
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