Analog gauges are often used in industrial settings to measure various process variables such as pressure, temperature, and flow. In many cases, analog gauges are preferred over digital gauges because most analog gauges mounted on old machinery cannot be easily replaced or it would be too costly to do so. However, they have several disadvantages, such as requiring visual inspection by a human operator for reading them and the difficulty of integrating them into digital systems to automate tasks. Computer Vision and Machine Learning can be used to overcome these disadvantages by retrofitting analog gauges with digital readouts. Computer Vision systems can automatically take readings from analog meters and displays, eliminating the need for manual reading and recording. In addition, this method provides real-time continuous monitoring of analog values, allowing for more accurate trending and analysis, reducing maintenance times, and enabling defining alerts to prevent failures.