
Intelligent Environmental Data Monitoring for Pollution Management
- 344 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Intelligent Environmental Data Monitoring for Pollution Management
About this book
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
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Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- Preface
- 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: A critical review
- 7: An intelligent estimation model for water quality parameters assessment at Periyakulam Lake, South India
- 8: Recent trends in air quality prediction: An artificial intelligence perspective
- 9: Optimization 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: Codesign 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
- Index