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E-raamat: Intelligent Environmental Data Monitoring for Pollution Management

Edited by (VSB Technical University of Ostrava, Czech Republic), Edited by , Edited by (VB-Technical University of Ostrava, Ostrava, Czech Republic), Edited by (Professor in Environmental Science, Department of Environmental Science, The University of Burdwan, Burdwan, India), Edited by
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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.
  • 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
Contributors xiii
Preface xvii
1 Batch adsorption process in water treatment
1(24)
Jinat Aktar
1 Introduction
1(1)
2 Batch experiments
2(2)
3 Factors affecting adsorption process
4(4)
4 Mechanism in batch adsorption
8(1)
5 Adsorption isotherm
9(4)
6 Adsorption kinetics
13(4)
7 Thermodynamics
17(1)
8 Desorption studies
17(2)
9 Conclusion
19(1)
Acknowledgments
20(1)
Funding
20(1)
References
20(5)
2 Removal of heavy metals from industrial effluents by using biochar
25(24)
Manash Gope
Rajnarayan Saha
1 Introduction
25(1)
2 Industrial effluents and heavy metal pollution
26(1)
3 Conventional processes of removal heavy metals from effluent
26(4)
4 Biochar: The adsorbent
30(2)
5 Preparation of biochar
32(1)
6 Properties of biochar
33(1)
7 Removal of heavy metals by biochar
34(6)
8 Conclusion
40(2)
Acknowledgment
42(1)
References
42(7)
3 Nanoparticles: A new tool for control of mosquito larvae
49(22)
Arghadip Mondal
Priyanka Debnath
Naba Kumar Mondal
1 Introduction
49(1)
2 Nanoparticle synthesis
49(5)
3 Nanoparticle characterizations
54(6)
4 Application
60(5)
5 Research gap
65(1)
6 Conclusion
65(1)
Acknowledgments
66(1)
References
66(5)
4 Biosorption-driven green technology for the treatment of heavy metal(loids)-contaminated effluents
71(22)
Anirudha Paul
Jatindra N. Bhakta
1 Introduction
71(1)
2 Heavy metal(loid)s
72(2)
3 Conventional treatment process for metal(loid)s removal from wastewater
74(1)
4 Biosorption
75(1)
5 Mechanisms of biosorption
75(2)
6 Advantages of biosorption process
77(1)
7 Factors affecting biosorption
77(2)
8 Biosorption isotherm and model
79(1)
9 Biosorbent
79(3)
10 Modification of biosorbent
82(1)
11 Instrumentation involved in analysis of biosorption
83(1)
12 Conclusion
84(1)
References
84(9)
5 A comprehensive review of glyphosate adsorption with factors influencing mechanism: Kinetics, isotherms, thermodynamics study
93(34)
Kamalesh Sen
Soumya Chattoraj
1 Introduction
93(4)
2 Adsorption study
97(17)
3 Comparative study of glyphosate in recent published paper
114(1)
4 Possible mechanism of adsorption
114(3)
5 Lack of area of glyphosate adsorption
117(1)
6 Conclusion
118(1)
References
118(9)
6 Dyes and their removal technologies from wastewater: A critical review
127(34)
Mouni Roy
Rajnarayan Saha
1 Introduction
127(4)
2 Dye removal technologies
131(18)
3 Comparison between different treatment processes
149(1)
4 Conclusion and future perspective
149(3)
Acknowledgment
152(1)
References
152(9)
7 An intelligent estimation model for water quality parameters assessment at Periyakulam Lake, South India
161(34)
T.T. Dhivyaprabha
P. Subashini
M. Krishnaveni
N. Santhi
Ramesh Sivanpillai
G. Jayashree
1 Introduction
161(4)
2 Materials and methods
165(1)
3 Statistical analysis for water quality assessment
166(5)
4 Proposed methodology
171(7)
5 Experimental observations and discussions
178(14)
6 Conclusion
192(1)
References
192(3)
8 Recent trends in air quality prediction: An artificial intelligence perspective
195(28)
Ibrahim Kok
Metehan Guzel
Suat Ozdemir
1 Introduction
195(1)
2 Preliminary information
196(4)
3 Neural network-based prediction models
200(7)
4 Deep learning models for air quality prediction
207(9)
5 Conclusion
216(1)
References
217(6)
9 Optimization of absorption process for exclusion of carbaryl from aqueous environment using natural adsorbents
223(8)
Soumya Chattoraj
Kamalesh Sen
1 Introduction
223(1)
2 Characterization of adsorbents
224(1)
3 Adsorption study
225(2)
4 Conclusion
227(1)
References
227(4)
10 Artificial neural network: An alternative approach for assessment of biochemical oxygen demand of the Damodar River, West Bengal, India
231(10)
Tarakeshwar Senapati
Palas Samanta
Ritabrata Roy
Tarun Sasmal
Apurba Ratan Ghosh
1 Background
231(1)
2 Material and methods
232(4)
3 Results and discussion
236(3)
4 Conclusion
239(1)
Acknowledgments
239(1)
References
239(1)
Further reading
240(1)
11 Codesign to improve IAQ awareness in classrooms
241(28)
Bradley McLaughlin
Stephen Snow
Adriane Chapman
1 Introduction
241(1)
2 Related work
242(4)
3 Methodology
246(3)
4 System design and implementation
249(8)
5 Understanding system use
257(5)
6 Discussion
262(2)
7 Conclusion
264(1)
References
265(4)
12 Data perspective on environmental mobile crowd sensing
269(20)
Mariem Brahem
Hafsa E.L. Hafyani
Souheir Mehanna
Karine Zeitouni
Laurent Yeh
Yehia Taher
Zoubida Kedad
Ahmad Ktaish
Mohamed Chachoua
Cyril Ray
1 Introduction
269(2)
2 Taxonomy
271(2)
3 Challenges of MCS
273(2)
4 Related work/projects
275(6)
5 Potential solutions
281(4)
6 Conclusion and research perspectives
285(1)
Acknowledgments
286(1)
References
286(3)
13 A survey of adsorption process parameter optimization related to degradation of environmental pollutants
289(22)
Anindya Banerjee
Avedananda Ray
1 Introduction
289(1)
2 Motivation and contributions
290(1)
3 Neural networks
290(4)
4 Path analysis
294(1)
5 Neurofuzzy network analysis
295(2)
6 Response surface methodology
297(6)
7 Random forest model
303(1)
8 Stochastic gradient boosting
304(1)
9 Conclusion
305(1)
References
305(3)
Further reading
308(3)
Index 311
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 VB-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 VB-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.