Abstract
Bread is a product of the food industry. Making bread includes mixing ingredients into dough, fermentation, and baking. The time of the fermentation process affects the structure of the bread. The longer the fermentation time, the less sturdy the bread becomes, and vice versa. Therefore, this research developed a system to determine the fermentation level of bread dough using an electronic nose. This system involves seven gas sensors to detect the aroma produced by bread dough. The Arduino Nano microcontroller is employed to transform analog sensor signals into digital data transmitted to the computer. The convolution neural network (CNN) method is applied to determine the level of fermentation, which consists of unfermented, half-fermented, and fermented. Experimental results show that each fermentation level provides a different sensor response pattern. This system can also classify each level of fermentation with 100% accuracy.
Original language | English |
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Title of host publication | 2024 International Seminar on Intelligent Technology and Its Applications |
Subtitle of host publication | Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 616-620 |
Number of pages | 5 |
Edition | 2024 |
ISBN (Electronic) | 9798350378573 |
DOIs | |
Publication status | Published - 2024 |
Event | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia Duration: 10 Jul 2024 → 12 Jul 2024 |
Conference
Conference | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 |
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Country/Territory | Indonesia |
City | Hybrid, Mataram |
Period | 10/07/24 → 12/07/24 |
Keywords
- bread dough fermentation
- convolution neural network
- electronic nose
- food
- gas sensor