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AI-Based Smart Water Quality Monitoring and Wastewater Management: An Integrated Bio-Computational Approach
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Author(s): Dipankar Ghosh (JIS University, India), Sayan Adhikary (JIS University, India)and Srijaa Sau (JIS University, India)
Copyright: 2024
Pages: 25
Source title:
Innovations in Machine Learning and IoT for Water Management
Source Author(s)/Editor(s): Abhishek Kumar (Chandigarh University, India), Arun Lal Srivastav (Chitkara University, India), Ashutosh Kumar Dubey (University of Castilla-La Mancha, Spain), Vishal Dutt (AVN Innovations Pvt. Ltd., India)and Narayan Vyas (AVN Innovations Pvt. Ltd., India)
DOI: 10.4018/979-8-3693-1194-3.ch007
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Abstract
Water is unambiguously susceptible to contamination, as it is able to dissolve a broader spectrum of substances than any other liquid on Earth. Increasing population and urbanization have been imposed to monitor water quality and wastewater management in the current global scenario. Conventional water quality monitoring involves water sampling, testing, and investigation, which are usually performed manually and are not dependable. Rapid economic prosperity generates a larger quantity of wastewater enriched with a broad range of pollutants that pose serious threats to the environment and human health. Advancements in artificial intelligence and machine learning approaches have shown breakthrough potential toward large dataset capture and analysis of large datasets to attain complex large-scale water quality monitoring and wastewater management systems. The current chapter summarizes prospects and potentials of AI technologies for the amelioration of water quality monitoring and wastewater management to establish an integrated sustainable biocomputation platform in the near future.
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