Artificial Intelligence and Data Science in Environmental Sensing
eBook - ePub

Artificial Intelligence and Data Science in Environmental Sensing

  1. 324 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence and Data Science in Environmental Sensing

About this book

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. - Presents tools, connections and proactive solutions to take sustainability programs to the next level - Offers a practical guide for making students proficient in modern electronic data analysis and graphics - Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

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Yes, you can access Artificial Intelligence and Data Science in Environmental Sensing by Mohsen Asadnia, Amir Razmjou, Amin Beheshti, Mohsen Asadnia,Amir Razmjou,Amin Beheshti in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Title of Book
  2. Cover image
  3. Title page
  4. Table of Contents
  5. Copyright
  6. Contributors
  7. Editor Bio
  8. Preface
  9. Chapter 1 Smart sensing technologies for wastewater treatment plants
  10. Chapter 2 Advancements and artificial intelligence approaches in antennas for environmental sensing
  11. Chapter 3 Intelligent geo-sensing for moving toward smart, resilient, low emission, and less carbon transport
  12. Chapter 4 Language of response surface methodology as an experimental strategy for electrochemical wastewater treatment process optimization
  13. Chapter 5 Artificial intelligence and sustainability: solutions to social and environmental challenges
  14. Chapter 6 Application of multi-criteria decision-making tools for a site analysis of offshore wind turbines
  15. Chapter 7 Recent advances of image processing techniques in agriculture
  16. Chapter 8 Tuning swarm behavior for environmental sensing tasks represented as coverage problems
  17. Chapter 9 Machine learning applications for developing sustainable construction materials
  18. Chapter 10 The AI-assisted removal and sensor-based detection of contaminants in the aquatic environment
  19. Chapter 11 Recent progress in biosensors for wastewater monitoring and surveillance
  20. Chapter 12 Machine learning in surface plasmon resonance for environmental monitoring
  21. Index