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The thickness of the bacterial cellulose (BC) sheet is an important parameter that determines the end of the fermentation process. During the fermentation process, BC sheets produced will be visually visible. Commonly, the end of the fermentation process is determined using manual observation based on fermentation time and approximation of BC thickness which are subjective and susceptible to error especially for routine and large samples. To overcome those limitations, a new approach for accurate and real-time observation system to monitor the formation of BC thickness is developed in this research. The system can perform several tasks from image capturing and processing, image conversion to BC thickness, until data collection. The system is also able to send notification of fermentation conditions including BC thickness through the email system during the fermentation process regularly. The system consists of USB camera to capture image, the Python programming language to process image, and Raspberry Pi 3 installed with MySQL database to store the BC thickness data. Thickness calculation algorithm is compiled using python programming language and has succeeded in calculating various thickness of BC sheets during the fermentation process every 15 minutes for 8 days. The BC thickness data is automatically sent to the MySQL database and at the same time sent to user’s email.

New Approach for Observation of Bacterial Cellulose Sheet Formation Method using Image Processing