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Intelligent Environmental Data Monitoring for Pollution Management - 1st Edition - ISBN: 9780128196717

Intelligent Environmental Data Monitoring for Pollution Management

1st Edition

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Editors: Siddhartha Bhattacharyya Naba Kumar Mondal Jan Platos Vaclav Snasel Pavel Kromer
Paperback ISBN: 9780128196717
Imprint: Academic Press
Published Date: 1st November 2020
Page Count: 380
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Table of Contents

1. Batch Adsorption Process in Water Treatment

2. Removal of heavy metals from industrial effluents by using Biochar

3. Nanoparticles: A new tool for control of mosquito larvae

4. Biosorption driven green technology for the treatment of heavy metal (loids) contaminated effluents

5. A Comprehensive Review of Glyphosate Adsorption with Factors Influencing Mechanism: Kinetics, Isotherms, Thermodynamics Study

6. Dyes and their removal technologies from wastewater

7. An Intelligent Estimation Model for Water Quality Parameters Assesment at Periyakulam Lake, South India

8. Recent Trends in Air Quality Prediction: An Artificial Intelligence Perspective

9. Optimisation of absorption process for exclusion of Carbaryl from aqueous environment using natural adsorbents

10. Artificial Neural Network: An Alternative Approach for Assessment of Biochemical Oxygen Demand of the Damodar River, West Bengal, India

11. Co-design to improve IAQ awareness in classrooms

12. Data Perspective on Environmental Mobile Crowd Sensing

13. A Survey of Adsorption Process Parameter Optimization related to Degradation of Environmental Pollutants


Description

Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization.

Key Features

  • Introduces novel intelligent techniques needed to address environmental pollution for the well-being of the global environment
  • Offers perspectives on the design, development and commissioning of intelligent applications
  • Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies surrounding the monitoring and mitigation of environmental pollution
  • Puts forth insights on future generation intelligent pollution monitoring techniques

Readership

Academics and researchers interested in joining interdisciplinary projects on intelligent environmental data management


Details

No. of pages:
380
Language:
English
Copyright:
© Academic Press 2021
Published:
1st November 2020
Imprint:
Academic Press
Paperback ISBN:
9780128196717

Ratings and Reviews


About the Editors

Siddhartha Bhattacharyya

Siddhartha Bhattacharyya did his BS in Physics, B. Tech. and M. Tech. from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed his PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of several awards and is currently a Senior Research Scientist in VSB Technical University of Ostrava, Ostrava, Czechia. He is also the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is also serving as a Full Professor of Computer Application of the Institute. Prior to this, he was a Full Professor of Information Technology of RCC Institute of Information Technology, Kolkata, India. He served as the Head of the Department from March, 2014 to December, 2016. He is a co-author of 4 books and the co-editor of 16 books and has more than 200 research publications in international journals and conference proceedings. He is the Editor of International Journal of Pattern Recognition Research since January 2016 and the founding Editor in Chief of International Journal of Hybrid Intelligence; Publisher: Inderscience. His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing. Siddhartha is a life fellow of OSI, fellow of IETE and IEI, India.

Affiliations and Expertise

Professor, Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India

Naba Kumar Mondal

Dr. Naba Kumar Mondal is an Assistant Professor in Environmental Science, Department of Environmental Science, The University of Burdwan, Burdwan, India. He completed his post graduate in Chemistry from Department of Chemistry and doctorate degree in Environmental Science from Department of Environmental Science, The University of Burdwan. He has published his research work in more than 200 reputed international and national journals. His primary research interest are Adsorption Chemistry by low cost adsorbents, Water quality degradation and management in Arsenic and Fluoride affected areas of West Bengal, Indoor Air Pollution and Human Health, Nanotechnology and Mosquito control, Mobile tower radiation and Human health, and Teacher Education. Dr. Mondal has delivered several invited talks and key note addresses in national and international conferences of high repute.

Affiliations and Expertise

Assistant Professor in Environmental Science, Department of Environmental Science, The University of Burdwan, Burdwan, India

Jan Platos

Jan Platos received his Master's degree in Computer Science from the VSB-Technical University of Ostrava in the Czech Republic in 2006 and a PhD in Applied Mathematics from the same university in 2010. Jan became Associate Professor in Computer Science in 2014. Jan is interested in many areas of Computer Science, but his major fields are Data Compression and Bio-Inspired Algorithms. Moreover, he is also interested in Information Retrieval, Data Mining, Data Structures and Data Prediction. Jan is also active in the areas of Parallelization of the Algorithms by the Graphical Processing Units and Standard Multi-cores and Multiprocessor Servers. Jan is also focused in the application of different computer science algorithms and methods, and innovative approaches to difficult practical problems from any area. Jan is the co-author of more than 160 scientific papers published in proceedings and journals. Since April 2017, Jan has been Head of the Department of Computer Science at the Faculty of electrical Engineering and Computer Science. He also served as a Program Committee Member in more than 40 conferences around the world and as a reviewer for more than 7 journals.

Affiliations and Expertise

Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava, Czech Republic

Vaclav Snasel

Vaclav Snasel's research and development experience includes over 25 years in the Industry and Academia. He works in a multi-disciplinary environment involving artificial intelligence, multidimensional data indexing, conceptual lattice, information retrieval, semantic web, knowledge management, data compression, machine intelligence, neural network, web intelligence, data mining and applications to various real-world problems. He has authored/co-authored several refereed journal/conference papers and book chapters. In 2003 he became a visiting scientist in the Institute of Computer Science, Academy of Sciences of the Czech Republic. Since 2003 he has been vice-dean for Research and Science at Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Czech Republic. He has been a full professor since 2006. Before turning into a full time academic, he was working with industrial companies where he was involved in different industrial research and development projects for nearly 8 years. He received Ph.D. degree in Algebra and Geometry from Masaryk University, Brno, Czech Republic and a Master of Science degree from Palacky University, Olomouc, Czech Republic.

Affiliations and Expertise

Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Czech Republic

Pavel Kromer

Pavel Krömer, Ph.D. graduated in Computer Science at the Faculty of Electrical Engineering and Computer Science (FEECS) of VŠB-Technical University of Ostrava. He worked as an analyst, developer, and trainer in a private company between 2005 and 2010. Since 2010, he has worked at the Department of Computer Science, FEECS of VŠB-Technical University of Ostrava. In 2014, he was a Postdoctoral Fellow at the University of Alberta. In 2015, he was awarded the title Assoc. Professor of Computer Science. He was Researcher at the IT4Innovations (National Supercomputing Center) between 2011 and 2016 and has been a member of its scientific council since February 2017. Since 2017, he has been the Vice Dean for External Affairs at FEECS. Since 2018, he is a Senior Member of the IEEE. In his research, he focuses on computational intelligence, information retrieval, data mining, machine learning, soft computing and real-world applications of intelligent methods. In this field, he has also contributed to a number of major conferences organized by the IEEE and ACM.

Affiliations and Expertise

Faculty of Electrical Engineering and Computer Science, VŠB-Technical University, Ostrava, Czech Republic