AI-based IoT device for smart nation deployment
Hospitals are essential institutions that address the population’s healthcare needs. The workloads of nurses can be wide-ranging and stressful. Research has shown that a positive working environment helps nurses perform better at work, which translates to improved patients’ experiences. Hence, this...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/141243 |
| _version_ | 1826116614668419072 |
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| author | Foon, Si Han |
| author2 | Gan Woon Seng |
| author_facet | Gan Woon Seng Foon, Si Han |
| author_sort | Foon, Si Han |
| collection | NTU |
| description | Hospitals are essential institutions that address the population’s healthcare needs. The workloads of nurses can be wide-ranging and stressful. Research has shown that a positive working environment helps nurses perform better at work, which translates to improved patients’ experiences. Hence, this project aims to create a device based on machine learning applications to improve nurses’ workplace efficiency. This project seeks to implement a real-time audio classification system on the new platform of Google Coral. It should be able to classify four categories of sounds, namely shouting, coughing, speech, falling people, or objects. When deployed at hospital wards, the system acts as an additional safeguard for patients’ wellbeing by monitoring the surrounding soundscape for any health or safety concerns. The implementation of this project involves integrating software and hardware. It requires audio data pre-processing, feature extraction, and convolutional neural network model training. The trained model is tested as a sound acquisition and inferencing system on PC. For deployment to hardware, the model is converted to a lightweight, compatible form and run on the Linux based Coral device. |
| first_indexed | 2024-10-01T04:14:17Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/141243 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:14:17Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1412432023-07-07T18:36:31Z AI-based IoT device for smart nation deployment Foon, Si Han Gan Woon Seng School of Electrical and Electronic Engineering Smart Nation TRANS Lab EWSGAN@ntu.edu.sg Engineering::Electrical and electronic engineering Hospitals are essential institutions that address the population’s healthcare needs. The workloads of nurses can be wide-ranging and stressful. Research has shown that a positive working environment helps nurses perform better at work, which translates to improved patients’ experiences. Hence, this project aims to create a device based on machine learning applications to improve nurses’ workplace efficiency. This project seeks to implement a real-time audio classification system on the new platform of Google Coral. It should be able to classify four categories of sounds, namely shouting, coughing, speech, falling people, or objects. When deployed at hospital wards, the system acts as an additional safeguard for patients’ wellbeing by monitoring the surrounding soundscape for any health or safety concerns. The implementation of this project involves integrating software and hardware. It requires audio data pre-processing, feature extraction, and convolutional neural network model training. The trained model is tested as a sound acquisition and inferencing system on PC. For deployment to hardware, the model is converted to a lightweight, compatible form and run on the Linux based Coral device. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-05T04:43:17Z 2020-06-05T04:43:17Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141243 en A3089-191 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Foon, Si Han AI-based IoT device for smart nation deployment |
| title | AI-based IoT device for smart nation deployment |
| title_full | AI-based IoT device for smart nation deployment |
| title_fullStr | AI-based IoT device for smart nation deployment |
| title_full_unstemmed | AI-based IoT device for smart nation deployment |
| title_short | AI-based IoT device for smart nation deployment |
| title_sort | ai based iot device for smart nation deployment |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/141243 |
| work_keys_str_mv | AT foonsihan aibasediotdeviceforsmartnationdeployment |