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
1. Smart sensing technologies for wastewater treatment plants 2. Recent advancement in antennas for environmental sensing 3. Intelligent geo-sensing for moving toward smart, resilient, low emission, and less carbon transport 4. Language of Response Surface Methodology (RSM) as an experimental strategy for electrochemical wastewater treatment process optimization 5. Artificial intelligence and sustainability: Solutions to social and environmental challenges 6. Application of multi attribute decision making tools for site analysis of offshore wind turbines 7. Recent Advances of Image Processing Techniques in Agriculture 8. Applications of Swarm Intelligence in Environmental Sensing 9. Machine learning applications for developing sustainable construction materials 10. The AI-assisted removal process of contaminants in the aquatic environment 11. Recent progress in biosensors and data processing systems for wastewater monitoring and surveillance 12. Machine learning in surface plasmon resonance for environmental monitoring
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