Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

1st Edition - November 1, 2022

Write a review

  • Editors: Arun Srivastav, Ashutosh Dubey, Abhishek Kumar, Sushil Kumar Narang, Moonis Ali Khan
  • Paperback ISBN: 9780323997140

Purchase options

Purchase options
Available for Pre-Order
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer aided Artificial Intelligence and machine learning technologies as related to impacts of climate change and potential to prevent/remediate the effects. Different types of algorithms, mathematical relations, and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact and chances of improving and saving lives and creating a healthier world. These techniques are advancing and are being used in every field of science. Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e. climate action.

Key Features

  • Includes case studies on the application of AI and machine learning for monitoring climate change effects and management
  • Features applications of software and algorithms for modeling and forecasting climate change
  • Shows how real time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

Readership

Graduate students, research scholars and professionals working in the similar disciplines of climate science, environmental science, geological science, computer science etc. Researchers working in government agencies, industry, and NGOs

Table of Contents

  • Section A: Climate change and its adverse impacts
    1.Historical perspectives of climate change and its negative impacts on nature
    2. Monitoring of agricultural productions in climatic variations using artificial intelligence/machine learning
    3. Integration of traditional and advance techniques to mitigate the effects of climate change on the nature and human beings
    4. Socio-economic factors of climatic variations in developed countries
    5. Socio-economic factors of climatic variations in developing countries
    6. Effects of latitude on climate change and anticipated resilience
    7. Forecasting and management of disasters triggered by climate change
    8. Role of artificial intelligence in environmental sustainability
    9. Effects of climatic variations on the flora and fauna including human beings

    Section B: Climate change forecasting and its management
    10. Modelling/simulation and forecasting of climate change effects using artificial intelligence technique
    11. Effects and management of climate effects on water resources using artificial intelligence
    12. Climate change resilience practices for water resources
    13. Climate change resilience practices for agriculture sector
    14. Concept of climate smart villages using artificial intelligence/machine learning
    15. Role of artificial intelligence and machine learning techniques to enhance environmental sustainability
    16. Application of artificial intelligence and machine learning techniques for climate science education
    17. Application of artificial intelligence and machine learning techniques for energy efficiency
    18. Monitoring of the production of green fuels to achieve climatic sustainability using advance technologies
    19. Environmental decision support system and climate change resilience
    20. Forecasting of climate change effects on the oceans/seas levels using machine learning techniques
    21. Forecasting of climate change effects on the glaciers/ snow cover using machine learning techniques
    22. Significance of AI to develop mitigation strategies against climate change in accordance with sustainable development goal (climate action)

Product details

  • No. of pages: 400
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: November 1, 2022
  • Imprint: Elsevier
  • Paperback ISBN: 9780323997140

About the Editors

Arun Srivastav

Dr. Arun Lal Srivastav is an Assistant Professor at Chitkara University, Himachal Pradesh (India). He has obtained his Ph.D. from the Indian Institute of Technology (BHU), Varanasi, India on water treatment. Also, he has done post-doctoral research at National Chung Hsing University, Taiwan. He is currently involved in the teaching of Environmental Science, Environmental Engineering, and Disaster Management to the engineering students. His research interests include water treatment, climate change, river ecosystem, phytoremediation and waste management. He has published 51 research articles in journals, books and conferences. Currently, he is editing 7 books with the Elsevier and Wiley on river ecosystem, renewable energy, urban water crisis & management, climate change, green chemistry and e-waste management.

Affiliations and Expertise

Assistant Professor, Chitkara University School of Engineering and Technology, Chitkara University, Solan, Himachal Pradesh, India

Ashutosh Dubey

Dr. Ashutosh Kumar Dubey received his PhD degree in Computer Science and Engineering from JK Lakshmipat University, Jaipur, Rajasthan, India. He is currently in the department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He is also the Senior Member of IEEE and ACM. He has more than 14 years of teaching experience. He has authored a book name Database Management Concepts. He has been associated with many international and national conferences as the Technical Program Committee member. He is also associated as the Editor/Editorial Board Member/ Reviewer of many peer-reviewed journals. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence and Object-Oriented Programming.

Affiliations and Expertise

Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

Abhishek Kumar

Dr. Abhishek Kumar is doctorate in computer science from University of Madras and research is going on face recognition using IOT concept and done M.Tech in Computer Science & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 8 years with more than 50 publications in reputed, peer reviewed National and International Journals, books & Conferences. His research area includes Artificial intelligence, Image processing, Computer Vision, Data Mining and Machine Learning. He has been in International Conference Committee of many International conferences. He has been the reviewer/editor of various peer-reviewed journals.

Affiliations and Expertise

M.Tech in Computer Science and Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota, India

Sushil Kumar Narang

Sushil Kumar Narang is Dean and an Associate Professor in the Department of Computer Science & Engineering at Chitkara University, Rajpura, Punjab (India) since 2019. From 2006-2019, He was head of IT department at SAS Institute of IT & Research, Mohali, Punjab (India). From 1996-2006, He was Assistant Professor at Department of Computer Science & Applications, MLN College, Yamuna agar, Haryana (India).He has completed his Ph.D. at Panjab University, Chandigarh (India). His Research on “Feature Extraction and Neural Network Classifiers for Optical Character Recognition for Good quality hand written GurmukhiandDevnagariCharacters” focused on various image processing, machine as well as deep learning algorithms. His research interests lie in the area of programming languages, ranging from theory to design to implementation, Image Processing, Data Analytics and Machine Learning. He has collaborated actively with researchers in several other disciplines of computer science; particularly Machine Learning on real world use cases.He is a certified Deep Learning Engineer from Edureka. ​He possesses expertise in Object-Oriented Analysis & Design and Development using Java and Python programming using OpenCV in Image Processing and Neural Network construction. ​He has strong knowledge of C++ and Java with experience in component architecture of product interface. With Solid training and management skills, He has demonstrated proficiency in leading and mentoring individuals to maximize levels of productivity, while forming cohesive team environments.

Affiliations and Expertise

Department of Computer Science, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

Moonis Ali Khan

Moonis Ali Khan received his doctoral degree (Ph.D.) in Applied Chemistry from Aligarh Muslim University, Aligarh, India, in 2009. From 2009 to 2011, he worked as a Post-Doctoral Researcher at Yonsei University, South Korea and Universiti Putra Malaysia, Malaysia. In 2011, he joined the Chemistry Department at the King Saud University (KSU), Saudi Arabia as an Assistant Professor. Currently, he is working as an Associate Professor at KSU. He is an interfacial chemist and his research is focused on the synthesis and development of novel materials for environmental remediation applications. To date, he has guided two doctoral students for their respective degrees. He has published more than hundred (research and review) articles and has two U.S. patents to his credit.

Affiliations and Expertise

Associate Professor, College of Science, King Saud University, Riyadh, Saudi Arabia

Ratings and Reviews

Write a review

There are currently no reviews for "Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence"