Lightweight AI Framework for Industry 4.0 Case Study: Water Meter Recognition

The evolution of applications in telecommunication, network, computing, and embedded systems has led to the emergence of the Internet of Things and Artificial Intelligence. The combination of these technologies enabled improving productivity by optimizing consumption and facilitating access to real-...

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Bibliographic Details
Published in:Big data and cognitive computing 2022-09, Vol.6 (3), p.72
Main Authors: Ktari, Jalel, Frikha, Tarek, Hamdi, Monia, Elmannai, Hela, Hmam, Habib
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Automatic meter reading
Case studies
character recognition
Consumption
Data collection
Efficiency
Embedded systems
Factories
Human error
Industrial applications
Internet of Things
Machine learning
Manufacturing
Optical character recognition
predicted consumption
Productivity
Real time
Sensors
Smart cities
Smartphones
Value chain
Water consumption
water meter
Water meters
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Summary:The evolution of applications in telecommunication, network, computing, and embedded systems has led to the emergence of the Internet of Things and Artificial Intelligence. The combination of these technologies enabled improving productivity by optimizing consumption and facilitating access to real-time information. In this work, there is a focus on Industry 4.0 and Smart City paradigms and a proposal of a new approach to monitor and track water consumption using an OCR, as well as the artificial intelligence algorithm and, in particular the YoLo 4 machine learning model. The goal of this work is to provide optimized results in real time. The recognition rate obtained with the proposed algorithms is around 98%.
ISSN:2504-2289
2504-2289
DOI:10.3390/bdcc6030072