Augmented Digital Twins for Predictive Automatic Regulation and Fault Alarm in Sewage Plan
Pages 8495 - 8503
Abstract
In this paper, Digital Twins(DT) is combined with the sewage plant. Through Digital Twins, the actual needs are analyzed to solve the problems existing in the sewage plant. Combined with Augmented Reality(AR), Machine Learning(ML) and automatic control algorithms, various functions of sewage plant can be achieved. The system uses Long Short Term Memory(LSTM), Gate Recurrent Unit(GRU) and Fuzzy Neural Network(FNN) to predict the Chemical Oxygen Demand(COD) concentration in water quality. By using these algorithms, the Digital Twins Sewage Plant(DTSP) can be better interacted with workers. Through remote control, fault alarm, automatic regulation and prediction, Digital Twins can improve the efficiency of sewage treatment.
Supplemental Material
MP4 File
This video mainly introduces the formation process of a Digital Twins Sewage Plant. The video showcases the various functions of the Digital Twins Sewage Plant.
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Index Terms
- Augmented Digital Twins for Predictive Automatic Regulation and Fault Alarm in Sewage Plan
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Published In
October 2023
9913 pages
ISBN:9798400701085
DOI:10.1145/3581783
- General Chairs:
- Abdulmotaleb El Saddik,
- Tao Mei,
- Rita Cucchiara,
- Program Chairs:
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- Diana Patricia Tobon Vallejo,
- Pradeep K. Atrey,
- M. Shamim Hossain
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Published: 27 October 2023
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