  Electricity and gas meter reading is a time consuming task, which is done
manually in most cases. There are some approaches proposing use of smart meters
that report their readings automatically. However, this solution is expensive
and requires (1) replacement of the existing meters, even when they are
functional and new, and (2) large changes of the whole system dealing with the
meter readings. This paper presents results of a project on automation of the
meter reading process for the standard (non-smart) meters using computer vision
techniques, focusing on the comparison of two computer vision techniques,
Google Cloud Vision and AWS Rekognition.
