"IoT Applications Computing" ed. by Ishwar Singh, Carmine Massarelli, Zhen Gao
ITexLi | 2022 | ISBN: 1839686901 9781839686900 1839686898 9781839686894 183968691X 9781839686917 | 216 pages | PDF | 17 MB
ITexLi | 2022 | ISBN: 1839686901 9781839686900 1839686898 9781839686894 183968691X 9781839686917 | 216 pages | PDF | 17 MB
This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing.
The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable.
Contents
1. Radiofrequency Energy Harvesting for Wireless Sensor Node: Design Guidelines and Current Circuits Performance
2. Improved Multi Target Tracking in MIMO Radar System Using New Hybrid Monte Carlo–PDAF Algorithm
3. Vehicle Collision Avoidance System Using Li-Fi
4. The Role of Ubiquitous Computing in the Transformation of the Healthcare System
5. A Thermal and Energy Aware Framework with Physiological Safety Considerations for Internet of Things in Healthcare and Medical Applications
6. Environmental Management and Data for the SDGs
7. Impact of IoT on Renewable Energy
8. A Panglossian Dilemma
9. Internet of Things and Machine Learning Applications for Smart Precision Agriculture
10. Artificial Intelligence and Water Cycle Management
11. Analyses of Open Security Issues for Smart Home and Sensor Network Based on Internet of Things
12. IIoT Machine Health Monitoring Models for Education and Training
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