Suchergebnisse

Intro -- Foreword -- Contents -- About the Editor -- Smart Cities: Building Sustainable Cities -- 1 Introduction -- 2 Intelligent Cities: Smart Cities -- 3 Sustainable Cities -- 4 Methodology -- 5 Relationship Between Sustainable Cities and Intelligent Cities -- 6 From Smart Cities Toward Sustainable Cities: Inclusion and Life Quality -- 7 Case Studies: Smart Cities from Brazil and Portugal -- 8 Conclusion and Future Scope -- References -- Wearable Sensors for Smart Societies: A Survey -- 1 Introduction -- 2 Literature Survey -- 3 Conclusion -- References -- Postpandemic EdTech (Educational Technology) on Perspectives of Green Society -- 1 Introduction -- 2 Major Contribution -- 3 Technological Transformations in Education System -- 3.1 Online Video Lecture Platform -- 3.2 EdTech with Learning Applications -- 3.3 Virtual Transformation of Institutes -- 4 Technological Innovation of This Chapter -- 5 Education and Technology Complementary Approach -- 6 Future Technology Prospects -- 6.1 Education 4.0 -- 6.2 Industry 4.0 -- 6.3 Green Technology -- 7 Education Scenario of Pre- and Postpandemic Situation -- 8 Current Teaching-Learning as Blended Learning -- 9 Artificial Intelligence (AI)/Internet of Things (IoT)-Based EdTech -- 9.1 AI in Modern Education over Traditional Process -- 9.2 Existing AI Applications in Education -- 9.3 AI-Based Education Industry Perspectives -- 9.4 Scope of Industry to Develop Intelligent Education Platform -- 10 Holographic Technology and EdTech -- 10.1 Recording of Holograms -- 10.2 Use of Holograms in Virtual Teaching-Learning -- 10.3 Scope of 7D Technology to Form Virtual Institution -- 10.4 Benefits of Virtual Institution -- 10.5 AR/VR-Based Education in India -- 11 5G Technology in Blended Learning -- 12 Conclusion and Future Scope -- References.

The book Intelligent Healthcare: Infrastructure, Algorithms, and Management© cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue

Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- About the Editors -- List of Contributors -- Chapter 1 Healthcare Data Monitoring under Internet of Things -- 1.1 Introduction -- 1.1.1 Healthcare Data - Efficient Storage of Big Data -- 1.2 Digitization of Healthcare-Oriented Big Data -- 1.3 Healthcare - IoT and Mobile Health -- 1.4 Management of Big Data -- 1.4.1 Electronic Medical Record (EMR) or Electronic Health Record (EHR) -- 1.4.2 Healthcare Analytics -- 1.5 Medical Data Analysis and Disease Predictions through ML -- 1.6 Applications of Big Data in the Medical Field -- 1.7 Analytics of Medical Data in the Mercantile Platform -- 1.8 Related Work -- 1.9 Challenges and Constraints Related to Healthcare-Based Big Data Concepts (Including Privacy and Security Issue) -- 1.10 Conclusion and Future Trends -- References -- Chapter 2 A Framework for Emergency Remote Care and Monitoring Using Internet of Things -- 2.1 Introduction -- 2.2 The IoT Architecture and Applications -- 2.2.1 Stage 1 (Sensors/Actuators) -- 2.2.2 Stage 2 (Data Acquisition Systems) -- 2.2.3 Stage 3 (Edge Analytics) -- 2.2.4 Stage 4 (Cloud Analytics) -- 2.3 Literature Survey -- 2.4 A Proposed Framework for Emergency Remote Care and Monitoring Using Internet of Things -- 2.4.1 Parameters for Prediction -- 2.5 Proposed Work -- 2.6 Results and Discussion -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Big Data Analytics and K-Means Clustering -- 3.1 Introduction -- 3.2 Big Data -- 3.3 Predictive Analytics -- 3.4 Predictive Modeling -- 3.5 MapReduce Abstraction -- 3.6 Resilient Distributed Datasets (RDDs) -- 3.7 Computational Phenotyping -- 3.8 Clustering -- 3.9 Medicinal Oncology -- 3.10 Dimensionality Reduction -- 3.11 Patient Similarity -- 3.12 Distance Metric Learning -- 3.13 Graph-Based Similarity Learning.

Intro -- Preface -- Contents -- About the Editors -- Analytics of Multiple-Threshold Model for High Average-Utilization Patterns in Smart City Environments -- 1 Introduction -- 2 Review of Related Works -- 2.1 High Utility Itemset Mining (HUIM) -- 2.2 High Average-Utility Itemset Mining -- 2.3 Multi-threshold Pattern Mining Works -- 3 Background of HAUIM and Problem Statement -- 4 Designed Model and Pruning Stratrgies -- 4.1 Developed Closure Property -- 4.2 Proposed Multi-HAUIM Model -- 4.3 Designed Strategy 1 -- 4.4 Designed Strategy 2 -- 5 Experimental Evaluation -- 5.1 Runtime Evaluation -- 5.2 Evaluation of Candidate Size -- 5.3 Evaluation of the Used Memory -- 5.4 Evaluation of Scalability -- 6 Conclusion and Future Work -- References -- Artificial Intelligence and Machine Learning for Ensuring Security in Smart Cities -- 1 Introduction -- 1.1 Smart City Applications -- 1.2 Technologies Used in Smart Cities and Integrated Technology in the Smart City-Edge/Cloud -- 1.3 Security Loophole in Smart Cities -- 1.4 AI/ML Based Counter Measures -- 1.5 Open Issues, Challenges and Recommendation -- 1.6 Conclusion and Future Scope -- References -- Smart Cities Ecosystem in the Modern Digital Age: An Introduction -- 1 Introduction -- 2 Smart Cities Concepts -- 3 Smart Cities Applications -- 4 Importance of Big Data for Smart Cities -- 5 Blockchain for Smart Cities -- 6 Machine Learning for Smart Cities -- 7 Discussion -- 7.1 Challenges on the Implementation of Smart City -- 8 Trends and Future Directions -- 9 Conclusions -- References -- A Reliable Cloud Assisted IoT Application in Smart Cities -- 1 Introduction -- 2 Literature Survey -- 3 Previous Work -- 4 Proposed Architecture -- 5 Analysis of the Contribution -- 6 Future Work -- 7 Conclusion -- References -- Lightweight Security Protocols for Securing IoT Devices in Smart Cities.

This book covers the sustainability issues of a green environment towards economics and society in terms of alteration in industrial pollution levels, effect of reduced carbon emissions, changes in water bodies characteristics with respect to heavy metal contamination, monitoring of associated impact with respect to ecology and biodiversity, impact of reduced noise levels and air quality influences on human health, handling and management of biomedical waste. According to WHO, 80% of people living in urban areas are exposed to air exceeding safe limits. The advent of "sustainability" in development science has led planners to apply evolving notions of "sustainability" to the contemporary debate over how cities and regions should be revitalized, redeveloped, and reformed. Market allocation of resources, sustained levels of growth and consumption, an assumption that natural resources are unlimited and a belief that economic growth will "trickle down" to the poor have been its hallmarks. The recent advance technology helps to promote green and clean modern societies continuously. The Internet of things will be playing an important role in the upcoming years in environment protection and sustainable development. There is a focus on paradigm shift in the sustainable development for the green environment during the period of isolation of COVID-19. This is the moment for the mobilization against the climate crisis. The sudden fall in pollutants and subsequent blue skies signifies a dramatic shift for India and also other affected countries during this period. Fighting climate change requires a collaborative approach between all spheres of society unlike the former. It must heavily redirect resources towards local, sustainable activities, including education, health, sustainable agriculture and circular management of resources. The impact of COVID-19 pandemic which has resulted in the dramatic change in the different aspects of the environment. The global lockdown has led to a rejuvenation of nature, ecosystems, biodiversity. Even urban environments are discovering a degree of peace and serenity, which led to decrease in greenhouse gas emission.

"Digital technologies are a major sector to invest and research in new models of health management. Future health scenarios are constituted by technologies in health, and clinical decision-making systems. This book provides unique multidisciplinary approach for exploring the potential contribution of AI and digital technologies in enabling global healthcare systems to respond to urgent 21st century challenges. Deep analysis has been made regarding telemedicine using big data, deep learning, robotics, mobile and remote applications. Features: Focusses on prospective scenarios in health to foresight possible futures. Addresses the urgent needs of the key population, socio-technical, and health themes. Covers health innovative practices as 3D models for surgeries, big data to treat rare diseases, AI robot for heart treatments. Explores telemedicine using big data, deep learning, robotics, mobile and remote applications. Reviews public health based on predictive analytics and disease trends. This book is aimed at researchers, professionals and graduate students in computer science, artificial intelligence, decision support, healthcare technology management, biomedical engineering, and robotics"--