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Értesítés a kedvenc témákról
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System Design Using the Internet of Things with Deep Learning Applications

 
Kiadás sorszáma: 1
Kiadó: Apple Academic Press
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Rövid leírás:

Offers real-world solutions to present-day problems by using IoT and related technologies. It explores the diverse applications of the Internet of Things in diverse areas?in healthcare, the construction industry, in wildlife monitoring, in home security systems, in agriculture, in cryptology, in data security, and more.

Hosszú leírás:

This new volume aims to find real-world solutions to present-day problems by using IoT and related technologies. It explores the myriad applications of the Internet of Things in diverse areas?in healthcare, the construction industry, in wildlife monitoring, in home security systems, in agriculture, in cryptology, in hospitality employment, in data security, and more.


The chapters illustrate the defining aspects of architecture, product design, modules, interfaces, and data for building systems that satisfy specified requirements of the IoT applications discussed. The authors show the novel results that present solutions to meet the ever-increasing demand of industries.

Tartalomjegyzék:

1. Applications of the Internet of Things and Big Data in Automated Healthcare 2. IoT in the Construction Industry 3. Object Detection from Video Sequence and Its Analysis for Application in Wildlife 4. Design of a Flow Detection Sensor for Single-Phase Flow through Porous Media 5. Deep Neural Network-Based Brain Tumor Segmentation 6. Voice-Command-Based Real-Time Automated Home Security System with Google Assistance Technology 7. Applications of IoT and UAV in Smart Agriculture 8. A Study on Data Security in Cloud Computing: Traditional Cryptography to the Quantum Age Cryptography 9. Role of Hospitality Institutions in Development of Employability Expertise: Students? Perception Based on Data Analysis 10. Application of IoT and Big Data in Automated Healthcare 11. Forecast the Impact of COVID-19: Data Analysis 12. Comparative Analysis of SVM and KNN in Breast Cancer Classification