03984nam a22006135i 4500 978-3-031-54277-0 DE-He213 20251030111820.0 cr nn 008mamaa 240416s2024 sz | s |||| 0|eng d 9783031542770 978-3-031-54277-0 10.1007/978-3-031-54277-0 doi TA345-345.5 UN bicssc COM018000 bisacsh UN thema Data-Driven Innovation for Intelligent Technology [electronic resource] : Perspectives and Applications in ICT / edited by Hiram Ponce, Jorge Brieva, Octavio Lozada-Flores, Lourdes Martínez-Villaseñor, Ernesto Moya-Albor. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XII, 246 p. 68 illus., 59 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Studies in Big Data, 2197-6511 ; 148 Contactless Video-based Vital-sign Measurement Methods: A Data-driven Review -- Enhancing STEAM in Education 4.0: A Review of Data-driven Technological Improvements -- State-of-the-Art Review in Explainable Machine Learning for Smart-Cities Applications -- Exploring the Connection Between Digital Systems and Sustainability: Synergy for a Brighter Future. This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems. Engineering Data processing. Computational intelligence. 64052 Big data. 57216 Artificial intelligence. 58441 Data Engineering. 66059 Computational Intelligence. 64052 Big Data. 57216 Artificial Intelligence. 58441 Ponce, Hiram. editor. edt http://id.loc.gov/vocabulary/relators/edt Brieva, Jorge. editor. edt http://id.loc.gov/vocabulary/relators/edt 75254 Lozada-Flores, Octavio. editor. edt http://id.loc.gov/vocabulary/relators/edt 75255 Martínez-Villaseñor, Lourdes. editor. (orcid)0000-0002-9038-7821 https://orcid.org/0000-0002-9038-7821 edt http://id.loc.gov/vocabulary/relators/edt Moya-Albor, Ernesto. editor. (orcid)0000-0002-9637-786X https://orcid.org/0000-0002-9637-786X edt http://id.loc.gov/vocabulary/relators/edt 75256 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031542763 Printed edition: 9783031542787 Printed edition: 9783031542794 Studies in Big Data, 2197-6511 ; 148 68724 https://doi.org/10.1007/978-3-031-54277-0 ZDB-2-INR ZDB-2-SXIT 59159 59159