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Making Waves: Towards data-centric water engineering.

Guangtao Fu1, Dragan Savic2, David Butler1

  • 1Centre for Water Systems, University of Exeter, Exeter EX4 4QF, United Kingdom.

Water Research
|April 10, 2024
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) is driving a new era in water engineering. Data-centric approaches, powered by AI, will transform water resource management and infrastructure planning for a changing world.

Keywords:
Artificial intelligenceData-centricModel-centricScientific paradigmWater engineering

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Area of Science:

  • Environmental Engineering
  • Water Resources Management
  • Computer Science

Background:

  • Water engineering has evolved through empirical, theoretical, and computational paradigms.
  • Recent advances in artificial intelligence (AI) are enabling a new approach.
  • Addressing global water challenges requires innovative solutions.

Purpose of the Study:

  • To propose a framework for data-centric water engineering.
  • To outline the principles and requirements for this emerging paradigm.
  • To accelerate the adoption of AI in the water sector.

Main Methods:

  • Defining a data pipeline for transforming data into knowledge using AI.
  • Establishing core principles: data-first, integration, and decision-making.
  • Identifying needs for interdisciplinary collaboration and ethical frameworks.

Main Results:

  • A new framework for data-centric water engineering is presented.
  • AI technologies are central to the proposed data pipeline.
  • Three key principles guide this paradigm shift.

Conclusions:

  • Data-centric water engineering represents a significant paradigm shift.
  • Successful implementation requires interdisciplinary efforts, cultural change, and ethical guidelines.
  • This approach will fundamentally transform water infrastructure management.