Artificial Intelligence and Data Science in Environmental Sensing - Couverture souple

Couverture souple

ISBN 10 : 0323905080 ISBN 13 : 9780323905084

Editeur : Academic Press Inc, 2022

Synopsis

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.

A propos du livre

À propos des auteurs

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.

Amir Razmjou is an Associate Professor at Edith Cowan University and the Leader of the Mineral Recovery Research Centre (MRRC).

Associate Professor Amir Razmjou (PhD from the University of New South Wales (UNSW), Sydney, Australia, 2012) is an experienced academic and industry professional with over 20 years of expertise in desalination, water treatment, membrane technology, and mineral processing. As a Board Director of the Membrane Society of Australasia (MSA) and Founder of the Mineral Recovery Research Centre (MRRC) at Edith Cowan

University (ECU), Western Australia, Associate Professor Razmjou has made significant contributions to the fields of mining and resource extraction, particularly in lithium processing.

He has published over 200 peer-reviewed articles and secured research funding

exceeding $9.2 million AUD. Dr. Razmjou has received awards such as the 2024 WA FHRI

Fund Innovation Fellow, the 2023 MSA Industry Innovation Award, and the 2021 UTS Chancellor Research Fellow. He has supervised more than 40 master's and Ph.D. candidates and serves in editorial roles for journals such as Desalination, DWT, and JWPE. At MRRC, he has established a DLE line, including various processes such as membranes, ion exchange, and adsorption at laboratory and pilot scales. His research also includes developing and implementing advanced technologies for DLE's pretreatment and posttreatment to enhance the Li/TDS ratio and purify the final product to battery-grade

quality"

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.

Détails de l'édition

• Éditeur: Academic Press Inc
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 0323905080
• ISBN 13: 9780323905084
• Reliure: Broché
• Nombre de pages: 324
• Éditeur: Asadnia Mohsen, Razmjou Amir, Beheshti Amin
• Coordonnées du fabricant: Academic Press; https://shop.elsevier.com/; ; 230 PARK AVENUE, SUITE 800; NY; NY; 10169; Etats-Unis
• Personne responsable: Barbara Criscuolo; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; 20141; Italie