Artificial Intelligence and Data Science in Environmental Sensing (eBook, ePUB)

Redaktion: Asadnia, Mohsen; Beheshti, Amin; Razmjou, Amir

• Format: ePub

Produktbeschreibung

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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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 324
• Erscheinungstermin: 9. Februar 2022
• Englisch
• ISBN-13: 9780323905077
• Artikelnr.: 63418957

Autorenporträt

Mohsen Asadnia is a Professor and group lader in Mechatronics-biomechanics and at Macquarie University, Australia. He received his PhD degree in Mechanical Engineering from Nanyang Technological University, Singapore. Prior to joining Macquarie University, Mohsen had several teaching and research roles with the University of Western Australia, Massachusetts Institute of Technology and Nanyang Technological University. His research interest lies in environmental/ biomedical sensors, Artificial Intelligence, and bio-inspired sensing.

Amin Beheshti is a Full Professor of Data Science and the Director of AI-enabled Processes (AIP) Research Centre, School of Computing, Macquarie University. Amin is also the head of the Data Analytics Research Lab and Adjunct Academic in Computer Science at UNSW Sydney. Amin completed his Ph.D. and Postdoc in Computer Science and Engineering at UNSW Sydney and holds a Master and Bachelor in Computer Science both with First Class Honours. He is the leading author of several authored books in data, social, and process analytics, co-authored with other high-profile researchers.

Inhaltsangabe

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

Rezensionen

04
. Machine learning in surface plasmon resonance for environmental monitoring