Description
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
Table of Contents
1. Smart sensing technologies for wastewater treatment plants2. Recent advancement in antennas for environmental sensing3. Intelligent geo-sensing for moving toward smart, resilient, low emission, and less carbon transport4. Language of Response Surface Methodology (RSM) as an experimental strategy for electrochemical wastewater treatment process optimization5. Artificial intelligence and sustainability: Solutions to social and environmental challenges6. Application of multi attribute decision making tools for site analysis of offshore wind turbines7. Recent Advances of Image Processing Techniques in Agriculture8. Applications of Swarm Intelligence in Environmental Sensing9. Machine learning applications for developing sustainable construction materials10. The AI-assisted removal process of contaminants in the aquatic environment11. Recent progress in biosensors and data processing systems for wastewater monitoring and surveillance12. Machine learning in surface plasmon resonance for environmental monitoring
