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.
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.
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
Siddhartha Bhattacharyya is a Senior Researcher in the Faculty of
Electrical Engineering and Computer Science of VSB Technical
University of Ostrava, Czech Republic. He is also serving as the
Scientific Advisor of Algebra University College, Zagreb, Croatia.
Prior to this, he served as the Principal of Rajnagar
Mahavidyalaya, Rajnagar, Birbhum. He was a professor at CHRIST
(Deemed to be University), Bangalore, India, and also served as the
Principal of RCC Institute of Information Technology, Kolkata,
India. He is the recipient of several coveted national and
international awards. He received the Honorary Doctorate Award (D.
Litt.) from the University of South America and the SEARCC
International Digital Award ICT Educator of the Year in 2017. He
was appointed as the ACM Distinguished Speaker for the tenure
2018-2020. He has been appointed as the IEEE Computer Society
Distinguished Visitor for the tenure 2021-2023. He has co-authored
six books, co-edited 75 books, and has more than 300 research
publications in international journals and conference proceedings
to his credit. Dr. Naba Kumar Mondal is a 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. Jan Platos received a
Ph.D. in computer science in 2010. He became a Full professor in
2021 at the Department of Computer Science. Since 2021, he has been
Dean of the Faculty of Electrical Engineering and Computer Science,
VSB-TUO. He has co-authored more than 240 scientific articles
published in proceedings and journals. His primary fields of
interest are machine learning, artificial intelligence, industrial
data processing, text processing, data compression, bioinspired
algorithms, information retrieval, data mining, data structures,
and data prediction.
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.
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.
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