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https://hdl.handle.net/10356/77286
Title: | Artificial intelligence monitoring at the edge for smart nation deployment | Authors: | Wang, Ziao | Keywords: | DRNTU::Engineering::Electrical and electronic engineering | Issue Date: | 2019 | Abstract: | Artificial Intelligence Monitoring at the Edge basically monitors the urban noise classes and sound pressure level in Singapore urban area. In this project, I processed raw Singapore urban noise data collected from Yuhua garden and trained the classifier for 8 different classes of Singapore urban noise with processed noise data using machine learning method. Five different machine learning models are used to train the classifier and their performance are compared to find out the optimizing model under this noise classification scenario. | URI: | http://hdl.handle.net/10356/77286 | Schools: | School of Electrical and Electronic Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Student Reports (FYP/IA/PA/PI) |
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File | Description | Size | Format | |
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FYP_Wang_Ziao_final_version.pdf Restricted Access | 1.61 MB | Adobe PDF | View/Open |
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