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Authors: Maria Spichkova ; Johan van Zyl ; Siddharth Sachdev ; Ashish Bhardwaj and Nirav Desai

Affiliation: School of Science, RMIT University, Melbourne and Australia

Keyword(s): Software Engineering, Computer Vision, Google Cloud Vision, AWS Rekognition.

Related Ontology Subjects/Areas/Topics: Application Integration Technologies ; Applications ; Software Engineering

Abstract: 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.

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Paper citation in several formats:
Spichkova, M.; van Zyl, J.; Sachdev, S.; Bhardwaj, A. and Desai, N. (2019). Easy Mobile Meter Reading for Non-smart Meters: Comparison of AWS Rekognition and Google Cloud Vision Approaches. In Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-375-9; ISSN 2184-4895, SciTePress, pages 179-188. DOI: 10.5220/0007762301790188

@conference{enase19,
author={Maria Spichkova. and Johan {van Zyl}. and Siddharth Sachdev. and Ashish Bhardwaj. and Nirav Desai.},
title={Easy Mobile Meter Reading for Non-smart Meters: Comparison of AWS Rekognition and Google Cloud Vision Approaches},
booktitle={Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2019},
pages={179-188},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007762301790188},
isbn={978-989-758-375-9},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Easy Mobile Meter Reading for Non-smart Meters: Comparison of AWS Rekognition and Google Cloud Vision Approaches
SN - 978-989-758-375-9
IS - 2184-4895
AU - Spichkova, M.
AU - van Zyl, J.
AU - Sachdev, S.
AU - Bhardwaj, A.
AU - Desai, N.
PY - 2019
SP - 179
EP - 188
DO - 10.5220/0007762301790188
PB - SciTePress

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