Application of Artificial Intelligence in the Management of Drinking Water: A Narrative Review

被引:4
作者
Maroju, Revathi G. [1 ]
Choudhari, Sonali G. [2 ]
Shaikh, Mohammed Kamran [1 ]
Borkar, Sonali K. [1 ]
Mendhe, Harshal [1 ]
机构
[1] Datta Meghe Inst Higher Educ & Res DU, Datta Meghe Med Coll, Dept Community Med, Nagpur, India
[2] Datta Meghe Inst Higher Educ & Res Ctr DU, Jawaharlal Nehru Med Coll, Dept Community Med, Wardha, India
关键词
machine learning; artificial intelligence; water management; safe water; waterborne diseases; RISK;
D O I
10.7759/cureus.49344
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Waterborne illnesses are a significant concern worldwide. The management of water resources can be facilitated by artificial intelligence (AI) with the help of data analytics, regression models, and algorithms. Achieving the Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development of the United Nations depends on understanding, communicating, and measuring the value of water and incorporating it into decision-making. Various barriers are used from the source to the consumer to prevent microbiological contamination of drinking water sources or reduce contamination to levels safe for human health. Infrastructure development and capacity-building policies should be integrated with guidelines on applying AI to problems relating to water to ensure good development outcomes. Communities can live healthily with such technology if they can provide clean, economical, and sustainable water to the ecosystem as a whole. Quick and accurate identification of waterborne pathogens in drinking and recreational water sources is essential for treating and controlling the spread of water-related diseases, especially in resource-constrained situations. To ensure successful development outcomes, policies on infrastructure development and capacity building should be combined with those on applying AI to water -related problems. The primary focus of this study is the use of AI in managing drinking water and preventing waterborne illness.
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页数:7
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共 43 条
  • [1] Evaluation of artificial intelligence models for flood and drought forecasting in arid and tropical regions
    Adikari, Kasuni E.
    Shrestha, Sangam
    Ratnayake, Dhanika T.
    Budhathoki, Aakanchya
    Mohanasundaram, S.
    Dailey, Matthew N.
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2021, 144
  • [2] Modelling and Prediction of Water Quality by Using Artificial Intelligence
    Al-Adhaileh, Mosleh Hmoud
    Alsaade, Fawaz Waselallah
    [J]. SUSTAINABILITY, 2021, 13 (08)
  • [3] New alginate-based interpenetrating polymer networks for water treatment: A response surface methodology based optimization study
    Al-Sakkari, Eslam G.
    Abdeldayem, Omar M.
    Genina, Eslam E.
    Amin, Lobna
    Bahgat, Nouran T.
    Rene, Eldon R.
    El-Sherbiny, Ibrahim M.
    [J]. INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES, 2020, 155 : 772 - 785
  • [4] [Anonymous], 2020, Where AI is Aiding Productivity
  • [5] [Anonymous], 2023, DRINK WAT
  • [6] [Anonymous], 2023, What is Artificial Intelligence in 2023? Types, Trends, and Future of it?
  • [7] [Anonymous], 2023, Interactive dialogue 2: Water for Sustainable Development
  • [8] [Anonymous], 2015, IBM builds a smarter planet
  • [9] [Anonymous], 2023, Definition of artificial intelligence
  • [10] [Anonymous], 2021, The Promise of Artificial Intelligence in Water Management