Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition
The purpose of this research encompasses two primary objectives: (1) Designing a smart cooking and kitchen safety system using Arduino Nanotechnology and voice recognition, and (2) Implementing these technologies in practical applications for smart cooking and kitchen safety. The aim is to develop a...
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Universitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian Masyarakat
2024-06-01
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| Series: | Inspiration |
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| Online Access: | https://ojs.unitama.ac.id/index.php/inspiration/article/view/73 |
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| author | Jumriati Jum Abdul Latief Imran Taufiq |
| author_facet | Jumriati Jum Abdul Latief Imran Taufiq |
| author_sort | Jumriati Jum |
| collection | DOAJ |
| description | The purpose of this research encompasses two primary objectives: (1) Designing a smart cooking and kitchen safety system using Arduino Nanotechnology and voice recognition, and (2) Implementing these technologies in practical applications for smart cooking and kitchen safety. The aim is to develop a kitchen security system that employs Arduino Nano and voice recognition to automatically control conventional LPG stoves with on-off functionality. Data collection methods included observation, interviews, and literature review. Cooking tests were conducted with chicken curry, vegetable soup, and tuna, each cooked three times to determine average cooking times. Cooking 2 kg of chicken took an average of 35.38 minutes, with a maturity level delay of 18 minutes, while 1 kg of chicken took 20 minutes, with an 8-minute delay. For 20 portions of vegetable soup, the average cooking time was 32.20 minutes, with a 7-minute delay, and for 5 portions, it was 15 minutes, with a 4-minute delay. Cooking 2 kg of tuna took an average of 26 minutes, with a 16-minute delay, and 1 kg took 13.25 minutes, with a 5-minute delay. Voice command testing showed a high success rate at distances ranging from 10 cm to 70 cm. The confusion matrix results indicated that the model accurately detected successful commands with high precision (88.89%) and good recall (81.63%). However, the model had difficulty identifying failed commands, achieving only 2 true negatives out of 20 negative data points. |
| format | Article |
| id | doaj-art-5948a5a495bf45c8bf598d1d6a795600 |
| institution | Kabale University |
| issn | 2088-6705 2621-5608 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Universitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian Masyarakat |
| record_format | Article |
| series | Inspiration |
| spelling | doaj-art-5948a5a495bf45c8bf598d1d6a7956002025-01-28T05:47:58ZengUniversitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian MasyarakatInspiration2088-67052621-56082024-06-01141879510.35585/inspir.v14i1.7373Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice RecognitionJumriati Jum0Abdul Latief1Imran Taufiq2Universitas Handayani MakassarUniversitas Handayani MakassarUniversitas Handayani MakassarThe purpose of this research encompasses two primary objectives: (1) Designing a smart cooking and kitchen safety system using Arduino Nanotechnology and voice recognition, and (2) Implementing these technologies in practical applications for smart cooking and kitchen safety. The aim is to develop a kitchen security system that employs Arduino Nano and voice recognition to automatically control conventional LPG stoves with on-off functionality. Data collection methods included observation, interviews, and literature review. Cooking tests were conducted with chicken curry, vegetable soup, and tuna, each cooked three times to determine average cooking times. Cooking 2 kg of chicken took an average of 35.38 minutes, with a maturity level delay of 18 minutes, while 1 kg of chicken took 20 minutes, with an 8-minute delay. For 20 portions of vegetable soup, the average cooking time was 32.20 minutes, with a 7-minute delay, and for 5 portions, it was 15 minutes, with a 4-minute delay. Cooking 2 kg of tuna took an average of 26 minutes, with a 16-minute delay, and 1 kg took 13.25 minutes, with a 5-minute delay. Voice command testing showed a high success rate at distances ranging from 10 cm to 70 cm. The confusion matrix results indicated that the model accurately detected successful commands with high precision (88.89%) and good recall (81.63%). However, the model had difficulty identifying failed commands, achieving only 2 true negatives out of 20 negative data points.https://ojs.unitama.ac.id/index.php/inspiration/article/view/73smart cookingarduinovoice recognitioninternet of things |
| spellingShingle | Jumriati Jum Abdul Latief Imran Taufiq Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition Inspiration smart cooking arduino voice recognition internet of things |
| title | Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition |
| title_full | Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition |
| title_fullStr | Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition |
| title_full_unstemmed | Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition |
| title_short | Smart Cooking and Kitchen Safety Using Arduino Nanotechnology and Voice Recognition |
| title_sort | smart cooking and kitchen safety using arduino nanotechnology and voice recognition |
| topic | smart cooking arduino voice recognition internet of things |
| url | https://ojs.unitama.ac.id/index.php/inspiration/article/view/73 |
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