Author(s)

Lin Zihan

Corresponding Author

Lin Zihan

Abstract

As the brewing industry enters a new era, developing high quality has become an essential task today. Based on the video analysis technology of deep learning, this paper aims to develop an intelligent beer brewing monitoring system to meet the quality and efficiency requirements of the beer brewing process. Through the video analysis test platform, we successfully built a video analysis model. In addition, we have established a signal acquisition system and video analysis circuit to identify and classify raw materials and brewing equipment, as well as to detect and identify parameters and conditions. The experimental results show that the intelligent beer brewing monitoring system based on video analysis has high accuracy and practicability. It can help identify and classify key ingredients in the brewing process and also monitor and identify changes in process parameters, thereby improving quality and efficiency. However, we also recognize the limitations of video analysis models and the room for improvement in signal acquisition systems and video analysis circuits. Therefore, we emphasize further optimization of the model and collaborative integration of the system to better meet the needs of the beer brewing industry. To sum up, this paper provides an advanced monitoring system for the beer brewing industry through the application of video analysis, which is expected to help improve the quality and efficiency of beer brewing, promote the industry to move towards high-quality goals, and meet the needs of the industry.

Keywords

Video analysis; Deep learning; Intelligent beer brewing monitoring system; Brewing quality; Brewing efficiency