首页|New Artificial Intelligence Study Findings Reported from King Faisal University (Artificial Intelligence Technologies Revolutionizing Wastewater Treatment: Current Trends and Future Prospective)

New Artificial Intelligence Study Findings Reported from King Faisal University (Artificial Intelligence Technologies Revolutionizing Wastewater Treatment: Current Trends and Future Prospective)

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Data detailed on artificial intelligence have been presented. According to news originating from King Faisal University by NewsRx correspondents, research stated, “Integration of the Internet of Things (IoT) into the fields of wastewater treatment and water quality prediction has the potential to revolutionize traditional approaches and address urgent challenges, considering the global demand for clean water and sustainable systems.” Funders for this research include Deanship of Scientific Research, Vice Presidency For Graduate Studies And Scientific Research, King Faisal University, Saudi Arabia. The news editors obtained a quote from the research from King Faisal University: “This comprehensive article explores the transformative applications of smart IoT technologies, including artificial intelligence (AI) and machine learning (ML) models, in these areas. A successful example is the implementation of an IoT-based automated water quality monitoring system that utilizes cloud computing and ML methods to effectively address the above-mentioned issues. The IoT has been employed to optimize, simulate, and automate various aspects, such as monitoring and managing natural systems, water-treatment processes, wastewater-treatment applications, and water-related agricultural practices like hydroponics and aquaponics. This review presents a collection of significant water-based applications, which have been combined with the IoT, artificial neural networks, or ML and have undergone critical peer-reviewed assessment.”

King Faisal UniversityArtificial IntelligenceEmerging TechnologiesMachine LearningTechnology

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.7)
  • 138