Buch, Englisch, 324 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 540 g
Buch, Englisch, 324 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 540 g
ISBN: 978-0-323-90508-4
Verlag: William Andrew Publishing
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.
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
- Technische Wissenschaften Technik Allgemein Technik: Allgemeines
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Geowissenschaften Umweltwissenschaften Umweltwissenschaften
- Geowissenschaften Umweltwissenschaften Umwelttechnik
Weitere Infos & Material
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