eBook, ePUB

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

Beschreibung

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

Technische Details

• Geräte: eReader
• ohne Kopierschutz

Autor

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.

Produktdetails

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

Rezensionen

04
. Machine learning in surface plasmon resonance for environmental monitoring