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Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms

  • Desarkar A
  • Das A
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Abstract

This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients? records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data. Preface; Contents; IoT Based Healthcare; 1 Internet of Things Driven Connected Healthcare; Abstract; 1 Introduction; 2 Internet of Things Architecture; 3 Internet of Things Based Healthcare; 4 Internet of Things Applications in Healthcare; 5 Challenges and Future Perspectives; 6 Conclusion; References; 2 Internet of Things in HealthCare; Abstract; 1 Brief to the Internet of Things; 2 Introduction of Internet of Things in HealthCare; 2.1 Communication Between Devices; 2.1.1 Medical Body Area Network (MBAN's); 3 Nanotechnology in Internet of Things. 3.1 Architecture Requirement: HealthCare Ecosystem in Nanotechnology3.2 Internet of NanoTechnology Things: Health Application Requirements, Opportunities and Challenges; 4 Wearable Devices; 4.1 The Concept of Wearable Device; 4.2 Internet of Things for Personalized HealthCare; 4.3 Wearable Device Characteristics; 4.4 Interoperability Issues; 5 Conclusion; References; 3 Energy Efficient Network Design for IoT Healthcare Applications; Abstract; 1 Introduction; 2 Importance of Energy Efficiency in IoT Healthcare Applications; 2.1 IoT World Forum Reference Model. 2.2 Energy Constrained Nature of IoT Network2.3 Energy Constrained Nature of IoT Health Care Application; 3 Techniques to Improve Energy Efficiency; 3.1 Role of Hardware and Software in Improving Energy Efficiency; 3.2 Role of Protocols in Improving Energy Efficiency; 3.3 Physical Layer Technique to Improve Energy Efficiency; 3.4 Network Layer Technique to Improve Energy Efficiency; 3.5 Data Link Layer Technique to Improve Energy Efficiency; 3.6 Transport Layer Technique to Improve Energy Efficiency; 3.7 Application Layer Technique to Improve Energy Efficiency; 4 Proposed Network Architecture. 4.1 Adopting Real-Time Healthcare Scenario to Proposed Network Architecture Scenario4.2 Proposed Node Placement Technique; 4.3 Proposed Routing Technique; 4.4 Packet Format; 4.5 Route Selection by Destination Node Based in SNR Value; 4.6 Basic Assumptions in Proposed Network Architecture; 4.7 Performance Evaluation; 5 Conclusion; References; 4 Exploring Formal Strategy Framework for the Security in IoT towards e-Health Context using Computational Intelligence; Abstract; 1 Introduction; 1.1 Motivation; 1.2 About the Health Sensors; 2 Similar Works. 2.1 Model, Parameters and Relevance: Bio-Inspired Algorithm and Pheromone Map2.1.1 Properties and Validation of Pheromone Deposition on Internet of Things (IoT); 3 Proposed Algorithm: Pheromone Alert; 3.1 Formal Proposition: Pheromone Deposition; 3.1.1 Formal Proposition: Pheromone Evaporation; 3.2 Expected Output; 4 Data and Implementation; 4.1 Evaluation of Results; 4.2 Limitations and Future Scope; 5 Conclusion; Appendix; References; 5 Vitality of Robotics in Healthcare Industry: An Internet of Things (IoT) Perspective; Abstract; 1 Introduction; 2 Robotics; 2.1 History and Definition.

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Desarkar, A., & Das, A. (2017). Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms (pp. 159–197). https://doi.org/10.1007/978-3-319-49736-5_8

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