Dear Colleagues,
We are planning to come up with a volume on Intelligent Environmental Data Analysis and Pollution Management to be published by Elsevier in 2019.
Efficient monitoring of environmental data for the purpose of management of pollution has been on the helm of affairs given the vast amount of pollutants injected into the environment due to industrial affluent. The state-of-the-art methods rely on time intensive and costly batch procedures.
This book will unearth intelligent techniques in order to address issues related to effective monitoring and prediction of environmental data for faithful management and mitigation of environmental pollution. The book focus is on the overall well-being of the global environment for better sustenance and livelihood.
Topics of interest include but not limited to:
Introduction to Batch Data Technologies for Pollution Monitoring
Review of concepts of batch processes
Categories of environmental hazards
Fundamentals of Batch processes
Current techniques for collection, processing and abstraction of environmental data
Review on Intelligent Tools and Techniques
Neural networking algorithms
Deep learning techniques
Neuro-fuzzy techniques
Evolutionary techniques
Hybrid intelligent tools
Quantum inspired computational intelligent techniques
Data sensing applications for pollution management
Removal of heavy metals from industrial effluents by green synthesis
Removal of phenol, azo and non-azo dyes from industrial effluents
Isolation characterization of soil and water bacteria
Removal of pesticide and insecticide from agricultural runoff water
Applications for estimation of quality of nanoparticle to control pathogenic bacteria and fungus.
Statistical prediction of nanoparticle levels for controlling vector population
Intelligent frameworks for wastewater treatment
Air quality evaluation and air pollution control
Source-based noise abatement
Big data approaches to environmental data analysis
Efficient monitoring of environmental data for the purpose of management of pollution has been on the helm of affairs given the vast amount of pollutants injected into the environment due to industrial affluent. The state-of-the-art methods rely on time intensive and costly batch procedures.
This book will unearth intelligent techniques in order to address issues related to effective monitoring and prediction of environmental data for faithful management and mitigation of environmental pollution. The book focus is on the overall well-being of the global environment for better sustenance and livelihood.
Topics of interest include but not limited to:
Introduction to Batch Data Technologies for Pollution Monitoring
Review of concepts of batch processes
Categories of environmental hazards
Fundamentals of Batch processes
Current techniques for collection, processing and abstraction of environmental data
Review on Intelligent Tools and Techniques
Neural networking algorithms
Deep learning techniques
Neuro-fuzzy techniques
Evolutionary techniques
Hybrid intelligent tools
Quantum inspired computational intelligent techniques
Data sensing applications for pollution management
Removal of heavy metals from industrial effluents by green synthesis
Removal of phenol, azo and non-azo dyes from industrial effluents
Isolation characterization of soil and water bacteria
Removal of pesticide and insecticide from agricultural runoff water
Applications for estimation of quality of nanoparticle to control pathogenic bacteria and fungus.
Statistical prediction of nanoparticle levels for controlling vector population
Intelligent frameworks for wastewater treatment
Air quality evaluation and air pollution control
Source-based noise abatement
Big data approaches to environmental data analysis
Important Dates:
Proposal submission: 21st May, 2019 (extended)
Acceptance of proposals: 28th May, 2019
Full chapter submission: 15th July, 2019
Review notification: 15th August, 209
Final submission: 31st October, 2019
Interested contributors are requested to send 1-2 page abstract with references and author details to [log in to unmask].
Best regards,
Siddhartha Bhattacharyya
Editor
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Sender notified by Mailtrack 04/21/19, 10:58:37 PM |
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Sender notified by Mailtrack 05/10/19, 10:07:46 PM |