Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing
The proposed research aims to develop a novel approach to artificial intelligence (AI) for edge computing in the metaverse that puts the needs and goals of users and tasks at the centre. This approach, referred to as the Unified, User and Task (UUT) Centered AI, seeks to address the challenges...
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2023
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sg-ntu-dr.10356-1659452023-04-21T15:37:06Z Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing Hoo, Kah Jun Jun Zhao School of Computer Science and Engineering junzhao@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The proposed research aims to develop a novel approach to artificial intelligence (AI) for edge computing in the metaverse that puts the needs and goals of users and tasks at the centre. This approach, referred to as the Unified, User and Task (UUT) Centered AI, seeks to address the challenges of resource allocation and management in a highly dynamic and distributed environment, where multiple users with diverse demands and devices share the same network resources. The UUT Centered AI will leverage deep learning and reinforcement learning techniques to learn from user behaviour and task requirements and optimize network resource allocation accordingly. The research will evaluate the performance of the proposed approach through simulations and experiments using real-world datasets and scenarios. The expected outcome is a more efficient and effective edge computing system for the metaverse that can better meet the needs of users and tasks while maintaining network quality and security. Bachelor of Engineering (Computer Science) 2023-04-17T04:04:14Z 2023-04-17T04:04:14Z 2023 Final Year Project (FYP) Hoo, K. J. (2023). Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165945 https://hdl.handle.net/10356/165945 en application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Hoo, Kah Jun Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
description |
The proposed research aims to develop a novel approach to artificial intelligence (AI)
for edge computing in the metaverse that puts the needs and goals of users and
tasks at the centre. This approach, referred to as the Unified, User and Task (UUT)
Centered AI, seeks to address the challenges of resource allocation and
management in a highly dynamic and distributed environment, where multiple users
with diverse demands and devices share the same network resources. The UUT
Centered AI will leverage deep learning and reinforcement learning techniques to
learn from user behaviour and task requirements and optimize network resource
allocation accordingly. The research will evaluate the performance of the proposed
approach through simulations and experiments using real-world datasets and
scenarios. The expected outcome is a more efficient and effective edge computing
system for the metaverse that can better meet the needs of users and tasks while
maintaining network quality and security. |
author2 |
Jun Zhao |
author_facet |
Jun Zhao Hoo, Kah Jun |
format |
Final Year Project |
author |
Hoo, Kah Jun |
author_sort |
Hoo, Kah Jun |
title |
Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
title_short |
Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
title_full |
Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
title_fullStr |
Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
title_full_unstemmed |
Unified, user and task (UUT) centered artificial intelligence for metaverse edge computing |
title_sort |
unified, user and task (uut) centered artificial intelligence for metaverse edge computing |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/165945 |
_version_ |
1764208094156423168 |