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      1. Naturvetenskap och teknik
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      3. Miljöteknik

      Sustainable Smart Water Systems

      A Comprehensive Approach

      AvKamil Reza Khondakar,Hirak Mazumdar

      Häftad, Engelska, 2026

      1 740 kr

      Kommande

      Beskrivning

      Sustainable Smart Water Systems: A Comprehensive Approach is an essential guide for students and researchers dedicated to sustainable water management. This book thoroughly examines potential threats to water quality from industrial activities, agricultural practices, and climate change, and also addresses the vital regulations and policies governing smart water systems. With a deep dive into innovative technologies, particularly advanced sensors, readers will uncover cutting-edge advancements in water treatment, including membrane filtration, advanced oxidation processes, and green chemistry methods. The insightful chapters illustrate the transformative impact of artificial intelligence and big data analytics on water quality monitoring, prediction, and decision-making, and are enriched by compelling case studies. Moreover, the book explores the revolutionary use of Internet of Things (IoT) devices for real-time water quality monitoring and control, shedding light on the challenges and future research directions in this dynamic field.

      • AI- and IoT-enabled smart water monitoring for real-time quality assessment and predictive management.
      • Advanced nano and membrane technologies for sustainable and energy-efficient water treatment.
      • Smart solutions for urban and agricultural water systems using data-driven optimization.
      • Integrated focus on risk, policy, and future sustainability challenges in water ecosystems.

      Produktinformation

      • Utgivningsdatum:2026-10-01
      • Mått:191 x 235 x undefined mm
      • Vikt:450 g
      • Format:Häftad
      • Språk:Engelska
      • Antal sidor:320
      • Förlag:Elsevier Science
      • ISBN:9780443364709

      Utforska kategorier

      • Miljöteknik inom Naturvetenskap och teknik

      Mer om författaren

      Dr. Kamil Reza Khondakar is a distinguished researcher with over a decade of experience in interdisciplinary science, combining physics, biomedical engineering, materials science, and artificial intelligence. He completed four years of doctoral training at the University of Queensland, Australia after receiving IPRSS fellowship from Government of Australia. He worked as research fellow for four years at the National Physical Laboratory, India, supported by a prestigious Government of India grant. His research focuses on lab-on-chip technology, microfluidics, biosensors, and point-of-care diagnostics, contributing to over 50 peer-reviewed publications in high-impact journals such as Accounts of Chemical Research, ACS Nano, Advances in Colloid and Interface Science, BMEMat and Biosensors and Bioelectronics, Small, etc. Dr. Kamil has delivered invited lectures in the USA and Australia on lab-on-a-chip technology for cancer detection. He has edited three Elsevier books and serves as an editor for journals: Frontiers in Nanotechnology and Biosensors. As a peer reviewer for top journals and a mentor to young researchers, he plays a vital role in advancing scientific innovation and publishing worldwide. Dr. Hirak Mazumdar is a distinguished Biomedical Researcher and Algorithm Developer specializing in Computer Vision, Image Processing, and advanced Machine Learning Algorithms. He earned his PhD from Sogang University, South Korea, in collaboration with Samsung Mechatronics R&D. During his PhD, he developed comprehensive algorithms for fault detection in semiconductor sensors, enhancing defect prediction and manufacturing yield. His significant contributions include sensor correlation analysis and machine learning applications to improve wafer fabrication processes.Following his doctorate, Dr. Mazumdar was a Post-Doctoral Fellow at Cheongju National University, South Korea, where he worked on a Ministry of Semiconductor Design-funded project developing machine learning software for wafer testing. He then joined the University of Houston, Texas, as a Post-Doctoral Scientist on a Department of Energy project focused on groundwater contamination detection using machine learning.Dr. Mazumdar’s research spans industrial big data analysis, intelligent medical sensor devices, sensor manufacturing systems, and quality assurance through complex machine learning algorithms. He has industry experience with Samsung and Hyundai, specializing in machine learning and data fault analysis. His interests also include nanotechnology, nano biosensor simulation, computational biology, and biomedical image analysis, particularly in analyzing cell cultures.In his post-PhD work, Dr. Mazumdar has expanded into healthcare technology and sustainability, developing secure machine learning frameworks for early diagnosis, personalized health management, remote monitoring, and digital health platforms such as telemedicine and virtual clinics. His work aims to improve patient outcomes through predictive analytics and AI-driven disease prevention.Dr. Ajeet Kaushik is an Associate Professor of Chemistry at the Department of Chemistry, at Florida Polytechnic University, Florida, United States, as well as an ICS Fellow and Fulbright Specialist. Currently he is exploring nano-enabled technologies for health and environmental monitoring. He has authored or co-authored over 350 publications, published 14 edited books, and has 4 patents, as well as various other editorial roles and international collaborations. Dr. Kaushik’s research interests include green chemistry, catalysis, drug delivery systems, electrochemistry, sensors, and point-of-care sensing for sustainable health and the environment.

      Innehållsförteckning

      • 1. Introduction to sustainable smart water systems2. Sustainability risk assessment and management in water quality3. Sources of water pollution and its impact on ecosystems4. Smart sensors for water testing and quality assessment5. Nanoseparation techniques for sustainable water treatment6. Sustainable membrane technology for water treatment7. Design and implementation of an internet of things based water quality framework8. Artificial intelligence and big data application for drinking water quality monitoring9. Artificial intelligence driven approaches for sustainable urban water management10. Sustainable agriculture through AI and IoT-enabled smart water management11. Water quality regulations and policies for sustainable management12. Challenges and future directions in sustainable water ecosystems
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