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Convergence of Deep Learning and Artificial Intelligence in Internet of Things [Mīkstie vāki]

Edited by (Panipat Inst of Engg and Tech, India), Edited by (Beni-Suef Uni.), Edited by (Galgotias College of Engineering and Technology, India), Edited by (Maharishi Markandeshwar Uni, India), Edited by (Shobhit Uni, India)
  • Formāts: Paperback / softback, 312 pages, height x width: 234x156 mm, weight: 610 g, 21 Tables, black and white; 112 Line drawings, black and white; 57 Halftones, black and white; 128 Illustrations, color; 41 Illustrations, black and white
  • Sērija : Future Generation Information Systems
  • Izdošanas datums: 12-Mar-2025
  • Izdevniecība: CRC Press
  • ISBN-10: 1032410426
  • ISBN-13: 9781032410425
  • Mīkstie vāki
  • Cena: 66,41 €
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  • Formāts: Paperback / softback, 312 pages, height x width: 234x156 mm, weight: 610 g, 21 Tables, black and white; 112 Line drawings, black and white; 57 Halftones, black and white; 128 Illustrations, color; 41 Illustrations, black and white
  • Sērija : Future Generation Information Systems
  • Izdošanas datums: 12-Mar-2025
  • Izdevniecība: CRC Press
  • ISBN-10: 1032410426
  • ISBN-13: 9781032410425

This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology.

• Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things.

• Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe.

• Explores the importance of blockchain technology in the Internet of Things security issues.

• Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy.

• Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications.

This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further

discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.



The text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the internet of things. It further discusses applications of smart technologies in diverse sectors such as production, manufacturing, transport, and healthcare.

Chapter 1
Deep Learning Algorithms for Real-Time Healthcare Monitoring Systems

Chapter 2
Neural-Network Based An Efficient Hybrid Control Scheme For The Tracking
Control Of Autonomous Underwater Vehicles

Chapter 3
Integrated Storage Allocation and Privacy Preserve Deduplication Process Over
Cloud Using Dekey Method

Chapter 4
Internet of Things for Smart Cities: Application and challenges

Chapter 5
IoTBased Garbage Monitoring System with Proposed Machine Learning Model for
Smart City

Chapter 6
Application of Natural language Processing and IOT to emulate Virtual
Receptionist

Chapter 7
An Overview: - Understanding of Image Fusion

Chapter 8
Meta-Heuristics Algorithm For Optimization

Chapter 9
Internet of Medical Things devices: A Review

Chapter 10
COVID-19 Patient Remote Health Monitoring System using IoT

Chapter 11
Neural Network-Based Machine Learning Model for Prediction of Blood Alanine

Chapter 12
Hybrid Algorithm for detection of COVID-19 using CNN and SVM

Chapter 13
Deep Learning Algorithms for IoTBased Hybrid Sensor using Big Data Analytics

Chapter 14
Delineation of landslide hazard zones of a part of Sutlej basin in Himachal
Pradesh through frequency ratio model

Chapter 15
Crop Recommendation System using Machine Learning Algorithms

Chapter 16
Impacts of Artificial Intelligence, Deep Learning and Internet of Things

Chapter 17
A Support Vector Machine based Deep learning Approach for object detection

Chapter 18
Artificial intelligence and IOT based Electric Grid: Future of Micro Grid

Chapter 19
An Analysis of Artificial Intelligence Initiatives and Programmes in India

Chapter 20
A Vital Fusion of Internet-of-Medical Things and Blockchain to Transform Data
Privacy and Security