Detection of Control Valve Diagnosis and Pipeline Using Machine Learning

Machine learning has the potential for transforming the workplace across various industries. It can streamline repetitive tasks, improve decisionmaking, enhance safety, and increase operational efficiency. Rather than relying on static images from multiple angles to train object detection models, using video footage can simplify the process and reduce the need for large image datasets. Amazon Rekognition, a service from Amazon Web Services (AWS), leverages deep learning algorithms to analyze both images and videos. Its features include facial recognition, object detection and tracking, text recognition, and content moderation. In this project, AWS Rekognition is utilized to assess control valves and detect pipeline leaks. It also distinguishes between different types of control valves, such as normally open, normally closed, and those with positioners. This approach illustrates the effectiveness of video-based learning for object detection and the utility of cloud-based AI services in industrial diagnostics and monitoring.