Das H., Dey N., Balas V.E. (Eds.) Real-Time Data Analytics for Large Scale Sensor Data

Elsevier, Academic Press, 2020. — 405 p. — (Advances in Ubiquitous sensing applications for healthcare. Volume Six). — ISBN 978-0-12-818014-3.Rapid developments of sensor technology and automated control technology have contributed tremendously to the building of real-time intelligence systems. With the advancements in sensor technologies and machine-to-machine communications, the paradigm of the Internet of things (IoT) has seen a major boom. Over the past few years IoT-based applications and products have become more commonplace. With the proliferation of sensor deployment, the challenge of storing and managing massive data has eventually transformed to a challenge of decision-making using the collected data.
This is particularly true for real-time applications like industrial IoT, smart transportation systems, smart grids, robotics, and so on. However, with this progress a number of technologicaladvancements are required, especially for catering to the real-time requirements imposed by most IoT-based smart environments and intelligence systems.
Table of Contents
Internet of Things in healthcare: Smart devices, sensors, and systems related to diseases and health conditions
Real-time data analytics in healthcare using the Internet of Things
Lightweight code self-verification using return-oriented programming in resilient IoT
Monte-Carlo Simulation models for reliability analysis of low-cost IoT communication networks in smart grid
Lightweight ciphertext-policy attribute-based encryption scheme for data privacy and security in cloud-assisted IoT
Soft sensor with shape descriptors for flame quality prediction based on LSTM regression
Communication-aware edge-centric knowledge dissemination in edge computing environments
An effective blockchain-based, decentralized application for smart building system management
Privacy and security of Internet of Things devices
Software-Defined Networking for the Internet of Things: Securing home networks using SDN
Appendix 1. Implementation screenshots