Akademik Veri Yönetim Sistemi
9th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2025, Gaziantep, Türkiye, 27 - 28 Haziran 2025, (Tam Metin Bildiri)
In this study, an AI-based automatic baking process monitoring system developed with a focus on domestic production capacity is presented. Current ovens and food processing machines suffer from limited quality control due to dependency on foreign technologies. Most approaches in the literature are based solely on image data analysis and neglect the integration of environmental physical variables such as temperature. Furthermore, practical needs such as real-time intervention capability and operability on edge devices are often not adequately addressed. The proposed system processes both image and temperature sensor data simultaneously using multimodal data fusion methods, enabling high-precision evaluation of the baking process quality. The developed system addresses the gaps in the literature by integrating both image and temperature sensor data through multimodal data fusion, enabling more accurate and reliable monitoring of the cooking process. Additionally, it responds to practical application needs such as real-time intervention and operability on edge devices, filling the gap in this field.