Academic Press Artificial Intelligence and Data Science in Environmental Sensing (Cognitive Data Science in Sustainable Computing)

Product Description 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. Review Presents high-level information on various sensing systems and data processing platforms for environmental monitoring From the Back Cover <i>Artificial Intelligence and Data Science in Environmental Sensing</i> 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. About the Author Mohsen Asadnia is an Associate 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 received his PhD in Chemical Engineering from the University of new south wales, Australia in 2012 and since then he has accrued multidisciplinary skills to develop innovative technologies for biomedical and environmental applications. His surface architecturing skills using functional nanostructured materials alongside biofunctionalization have helped him to develop innovative membranes for desalination and water treatment, and nanobiosensors. 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.