04042nam a22005895i 4500 978-981-97-5365-9 DE-He213 20251030113113.0 cr nn 008mamaa 240928s2024 si | s |||| 0|eng d 9789819753659 978-981-97-5365-9 10.1007/978-981-97-5365-9 doi GE196 RNU bicssc SCI026000 bisacsh RNU thema Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications [electronic resource] / edited by V. Ajantha Devi. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. VII, 175 p. 81 illus., 73 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Contributions to Environmental Sciences & Innovative Business Technology, 2731-8311 Leveraging IoT Based CNN for Streamlining Business Application -- Intelligent Electric Vehicles: Leveraging AI-IoT for Sustainable Mobility -- Internet of Things Enabled Deep Convolutional Neural Network Model for Breast Cancer Classification -- Application of Machine Learning in Cyber Security: A Technological Perceptive -- Statistical Surveillance for Host-based Intrusion Detection System (HIDS): An Intelligent System for Automation -- IoT for Healthcare: A Sustainable Approach -- A NOVEL TRUST BASED FRAMEWORK FOR SECURED VANETs IN FUTURE -- Big Data and IOT based Flood Monitoring using Deep Neural Network -- Role of Artificial Intelligence in Design & Implementation of Healthcare Web Based Application “Carefree Bharat” focusing Sustainable Development. This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery. Sustainability. 57661 Internet of things. 58845 Machine learning. 55059 Big data. 57216 Artificial intelligence. 58441 Sustainability. 57661 Internet of Things. 58845 Machine Learning. 55059 Big Data. 57216 Artificial Intelligence. 58441 Devi, V. Ajantha. editor. edt http://id.loc.gov/vocabulary/relators/edt 85218 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819753642 Printed edition: 9789819753666 Printed edition: 9789819753673 Contributions to Environmental Sciences & Innovative Business Technology, 2731-8311 https://doi.org/10.1007/978-981-97-5365-9 ZDB-2-EES ZDB-2-SXEE 63813 63813