Easy Mobile Meter Reading for Non-Smart Meters: Comparison of AWS Rekognition and Google Cloud Vision Approaches
This addresses the time-consuming and costly manual meter reading process for utility companies and consumers, though it is incremental as it applies existing cloud vision services to a specific domain.
The paper tackled the problem of automating meter reading for non-smart meters by comparing Google Cloud Vision and AWS Rekognition computer vision techniques, achieving results that show both can effectively digitize readings without requiring hardware replacement.
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.