The modern ways in which the health of most old industrial systems is identified is through continuous monitoring of the various supporting devices that are mostly analog systems. These analog systems need to be kept under a continuous watch to make sure that there are no unnecessary surges in the system. This process requires a lot of trained manpower that needs to observe the meters at repeated intervals and ensure that there is no imminent danger to the power plant. This paper outlines an algorithm that can automatically identify the pointer gauge readings using images captured by a camera. This will help in providing a record of the readings for future reference by deploying an automatic approach based on computer vision and digital image processing. If we consider real world problems, like that of a Nuclear Power plant, where converting Analog systems to Digital Systems requires a lot of capital and change in infrastructure, an Analog Meter Reader is the most viable solution. This Analog Meter Reader replaces the conventional Human- Analog interface with an Analog-Digital interface that uses computer vision and gray-scaling techniques to convert the set of analog system images fed into the system into a digital value, thus converting an Analog system into a Digital system without changing the current systems in place. The system uses Circle and Edge Detection image processing techniques that are used for identifying and observing the current position of the needle in the meter and gives an output directly to the user interface where threshold values can be manipulated. For this project and with the given apparatus, we are able to achieve an accuracy of about 60%, however, with better equipment we can achieve higher accuracies. © 2020 SERSC.