{"title":"Role of AI&ML in Modernizing Water and Wastewater Treatment Processes","authors":"Rajneesh Kumar, Manish Kumar Goyal","doi":"10.1007/s11270-024-07618-z","DOIUrl":null,"url":null,"abstract":"<div><p>The necessity for practical, affordable, and sustainable solutions in water management, as well as the technical ability to tackle issues related to water and wastewater, have made artificial intelligence and machine learning an increasingly important part of the modernisation of water and wastewater treatment processes. This study describes basic ideas and precepts of artificial intelligence and machine learning and the difficulties with using traditional techniques. It also examines the application of artificial intelligence and machine learning approaches to the treatment of wastewater and water, emphasising their importance in energy efficiency, defect detection, infrastructure monitoring, optimisation, decision support, and integration with intelligent technologies. The future of water and wastewater management is expected to be shaped by artificial intelligence and machine learning systems that aim to address these constraints. Machine learning methods are investigated for predictive modelling, energy efficiency, defect detection, and infrastructure monitoring. In addition, this article provides case studies showing how artificial intelligence and machine learning are applied in practical situations, assesses their work, discusses obstacles and restrictions, and describes potential directions and new developments in this area. Future trends in water management focus on artificial intelligence-driven solutions. Artificial intelligence and machine learning has excellent potential to modernise water and wastewater treatment systems, providing ground-breaking solutions to the 21st-century challenges of increasing demand for sustainable water management.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":808,"journal":{"name":"Water, Air, & Soil Pollution","volume":"236 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water, Air, & Soil Pollution","FirstCategoryId":"6","ListUrlMain":"https://link.springer.com/article/10.1007/s11270-024-07618-z","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The necessity for practical, affordable, and sustainable solutions in water management, as well as the technical ability to tackle issues related to water and wastewater, have made artificial intelligence and machine learning an increasingly important part of the modernisation of water and wastewater treatment processes. This study describes basic ideas and precepts of artificial intelligence and machine learning and the difficulties with using traditional techniques. It also examines the application of artificial intelligence and machine learning approaches to the treatment of wastewater and water, emphasising their importance in energy efficiency, defect detection, infrastructure monitoring, optimisation, decision support, and integration with intelligent technologies. The future of water and wastewater management is expected to be shaped by artificial intelligence and machine learning systems that aim to address these constraints. Machine learning methods are investigated for predictive modelling, energy efficiency, defect detection, and infrastructure monitoring. In addition, this article provides case studies showing how artificial intelligence and machine learning are applied in practical situations, assesses their work, discusses obstacles and restrictions, and describes potential directions and new developments in this area. Future trends in water management focus on artificial intelligence-driven solutions. Artificial intelligence and machine learning has excellent potential to modernise water and wastewater treatment systems, providing ground-breaking solutions to the 21st-century challenges of increasing demand for sustainable water management.
期刊介绍:
Water, Air, & Soil Pollution is an international, interdisciplinary journal on all aspects of pollution and solutions to pollution in the biosphere. This includes chemical, physical and biological processes affecting flora, fauna, water, air and soil in relation to environmental pollution. Because of its scope, the subject areas are diverse and include all aspects of pollution sources, transport, deposition, accumulation, acid precipitation, atmospheric pollution, metals, aquatic pollution including marine pollution and ground water, waste water, pesticides, soil pollution, sewage, sediment pollution, forestry pollution, effects of pollutants on humans, vegetation, fish, aquatic species, micro-organisms, and animals, environmental and molecular toxicology applied to pollution research, biosensors, global and climate change, ecological implications of pollution and pollution models. Water, Air, & Soil Pollution also publishes manuscripts on novel methods used in the study of environmental pollutants, environmental toxicology, environmental biology, novel environmental engineering related to pollution, biodiversity as influenced by pollution, novel environmental biotechnology as applied to pollution (e.g. bioremediation), environmental modelling and biorestoration of polluted environments.
Articles should not be submitted that are of local interest only and do not advance international knowledge in environmental pollution and solutions to pollution. Articles that simply replicate known knowledge or techniques while researching a local pollution problem will normally be rejected without review. Submitted articles must have up-to-date references, employ the correct experimental replication and statistical analysis, where needed and contain a significant contribution to new knowledge. The publishing and editorial team sincerely appreciate your cooperation.
Water, Air, & Soil Pollution publishes research papers; review articles; mini-reviews; and book reviews.