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Transforming Water Quality Assessment: A Quantum AI Approach

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

Water quality assessment is one of the fundamental approaches to environmental management, which guarantees the steady provision of reliable water sources for both human consumption, water-intensive industries, and the preservation of aquatic environments. Common techniques of water quality analysis and testing might not be flawed, but they have preconditions like high costs and duration of testing. In the case of water quality assessment, the potential and practical use of Quantum AI is in a position to process and analyse more extensive and complex datasets. This includes current information gathered from different sources like the sensors, satellite pictures among others and past data. Thus, it can find patterns and relations that classical AI does not see, which would allow predicting further changes in water quality and detecting contaminations on time. This paper aims to discuss the basic concepts of quantum computing and its potential use in water quality monitoring and prediction. It subsequently provides a comprehensive review of existing AI-based water quality methods, highlighting their strengths and drawbacks.

Original languageEnglish
Title of host publicationCognitive Science and Technology
PublisherSpringer
Pages159-180
Number of pages22
DOIs
Publication statusPublished - 2025

Publication series

NameCognitive Science and Technology
VolumePart F73
ISSN (Print)2195-3988
ISSN (Electronic)2195-3996

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

Keywords

  • Classical AI
  • Environmental management
  • Quantum computing
  • Sensors
  • Water quality methods

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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