طراحی سیستم با استفاده از اینترنت اشیا با کاربردهای یادگیری عمیق (Team-IRA)

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. 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. Cover Half Title Title Page Copyright Page About the Editors Table of Contents Contributors Abbreviations Preface Introduction 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 Expertises: Students’ Perception Based on Data Analysis 10. Application of IoT and Big Data in Automated Healthcare 11. Forecasting the Impact of COVID-19: Data Analysis 12. Comparative Analysis of SVM and KNN in Breast Cancer Classification Index