Intelligent Environmental Data Monitoring for Pollution Management

個数:1
紙書籍版価格
¥29,370
  • 電子書籍

Intelligent Environmental Data Monitoring for Pollution Management

  • 言語:ENG
  • ISBN:9780128196717
  • eISBN:9780128199244

ファイル: /

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.- 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

Table of Contents

1. Batch Adsorption Process in Water Treatment2. Removal of heavy metals from industrial effluents by using Biochar3. Nanoparticles: A new tool for control of mosquito larvae4. Biosorption driven green technology for the treatment of heavy metal (loids) contaminated effluents5. A Comprehensive Review of Glyphosate Adsorption with Factors Influencing Mechanism: Kinetics, Isotherms, Thermodynamics Study6. Dyes and their removal technologies from wastewater7. An Intelligent Estimation Model for Water Quality Parameters Assesment at Periyakulam Lake, South India8. Recent Trends in Air Quality Prediction: An Artificial Intelligence Perspective9. Optimisation of absorption process for exclusion of Carbaryl from aqueous environment using natural adsorbents10. Artificial Neural Network: An Alternative Approach for Assessment of Biochemical Oxygen Demand of the Damodar River, West Bengal, India11. Co-design to improve IAQ awareness in classrooms12. Data Perspective on Environmental Mobile Crowd Sensing13. A Survey of Adsorption Process Parameter Optimization related to Degradation of Environmental Pollutants

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