Artificial intelligence monitoring at the edge for smart nation deployment
A key aspect of Smart Nation is the collection of data with the use of live monitoring, which is then sent for analysis using artificial intelligence algorithms to extract the desired information. This project aims to improve the model training process using data augmentation via mixing noise int...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167564 |
| _version_ | 1824454530616524800 |
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| author | Chua, Jeremy Chin Yew |
| author2 | Gan Woon Seng |
| author_facet | Gan Woon Seng Chua, Jeremy Chin Yew |
| author_sort | Chua, Jeremy Chin Yew |
| collection | NTU |
| description | A key aspect of Smart Nation is the collection of data with the use of live monitoring, which is then sent for analysis using artificial intelligence algorithms to extract the desired information.
This project aims to improve the model training process using data augmentation via mixing noise into the training data, then implement the model prediction in a Raspberry Pi. This allows for sensors or microphones to be installed in various strategic locations, capturing the audio type of interest such as loud noises like crashes or screams to regular noises such as traffic or footstep noises.
With this proof-of-concept system can help to eventually automate and streamline the process of noise and audio-related monitoring. |
| first_indexed | 2025-02-19T03:23:47Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/167564 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:23:47Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1675642023-07-07T17:45:06Z Artificial intelligence monitoring at the edge for smart nation deployment Chua, Jeremy Chin Yew Gan Woon Seng School of Electrical and Electronic Engineering EWSGAN@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence A key aspect of Smart Nation is the collection of data with the use of live monitoring, which is then sent for analysis using artificial intelligence algorithms to extract the desired information. This project aims to improve the model training process using data augmentation via mixing noise into the training data, then implement the model prediction in a Raspberry Pi. This allows for sensors or microphones to be installed in various strategic locations, capturing the audio type of interest such as loud noises like crashes or screams to regular noises such as traffic or footstep noises. With this proof-of-concept system can help to eventually automate and streamline the process of noise and audio-related monitoring. Bachelor of Engineering (Information Engineering and Media) 2023-05-31T04:10:02Z 2023-05-31T04:10:02Z 2023 Final Year Project (FYP) Chua, J. C. Y. (2023). Artificial intelligence monitoring at the edge for smart nation deployment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167564 https://hdl.handle.net/10356/167564 en A3100-221 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Chua, Jeremy Chin Yew Artificial intelligence monitoring at the edge for smart nation deployment |
| title | 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_short | Artificial intelligence monitoring at the edge for smart nation deployment |
| title_sort | artificial intelligence monitoring at the edge for smart nation deployment |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | https://hdl.handle.net/10356/167564 |
| work_keys_str_mv | AT chuajeremychinyew artificialintelligencemonitoringattheedgeforsmartnationdeployment |