Big Data Analytics for Smart Transport and Healthcare Systems (eBook)
XVII, 190 Seiten
Springer Nature Singapore (Verlag)
978-981-99-6620-2 (ISBN)
This book aims to introduce big data solutions in urban sustainability applications-mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.
Dr. Saeid Pourroostaei Ardakani is a Senior Lecturer in Computer Science at the University of Lincoln, UK. His research and teaching expertise centers on smart and adaptive computing and/or communication solutions to build collaborative/federated (sensory/feedback)systems in Internet of Things (IoT) applications and cloud environments. Saeid is also interested in (ML-enabled) Big Data processing and analysis applications. Saeid formerly worked at the University of Nottingham (China campus), 2019-2023, and ATU, 2015-2018 as an Assistant Professor in Computer Science. He received his PhD in Computer Science from the University of Bath focusing on data aggregation routing in Wireless Sensor Networks. His subject specialisms are: Internet of Things, Big Data Analysis, Distributed and Collaborative Computing, Sensory Systems, and Educational Technology.
Prof. Ali Cheshmehzangi is the World's top 2% field leader, recognised by Stanford University. He has recently taken a senior leadership and management role at Qingdao City University (QCU), where he is a Professor in Architecture and Urban Planning, Director of the Center for Innovation in Teaching, Learning, and Research, and Advisor to the school's international communications. Over 11 years at his previous institute, Ali was a Full Professor in Architecture and Urban Design, Head of the Department of Architecture and Built Environment, Founding Director of the Urban Innovation Lab, Director of Center for Sustainable Energy Technologies, and Director of Digital Design Lab. He was Visiting Professor and now Research Associate of the Network for Education and Research on Peace and Sustainability (NERPS) at Hiroshima University, Japan. Ali is globally known for his research on 'urban sustainability'. So far, Ali has published over 300 journal papers, articles, conference papers, book chapters, and reports. To date, he has 15 other published books.
This book aims to introduce big data solutions in urban sustainability applications-mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.
| Erscheint lt. Verlag | 3.12.2023 |
|---|---|
| Reihe/Serie | Urban Sustainability | Urban Sustainability |
| Zusatzinfo | XVII, 190 p. 75 illus., 72 illus. in color. |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Netzwerke | |
| Informatik ► Weitere Themen ► Bioinformatik | |
| Medizin / Pharmazie ► Gesundheitswesen | |
| Technik ► Fahrzeugbau / Schiffbau | |
| Wirtschaft | |
| Schlagworte | Big Data Analytics • Data Interpretation • Data Modeling • Data Science • Healthcare • Healthcare Optimisation • machine learning techniques • smart applications • Transportation Management • Transport Systems |
| ISBN-10 | 981-99-6620-5 / 9819966205 |
| ISBN-13 | 978-981-99-6620-2 / 9789819966202 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 8,5 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
