System Design Using the Internet of Things with Deep Learning Applications

by Arpan Deyasi (Editor), Angsuman Sarkar (Editor), Soumen Santra (Editor)

Overview

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.

Product Details

ISBN-13:	9781774912584
Publisher:	Apple Academic Press
Publication date:	10/06/2023
Pages:	282
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Arpan Deyasi, PhD, is Assistant Professor in the Department of Electronics and Communication Engineering at RCC Institute of Information Technology, Kolkata, India. He has 15 years of professional experience in academics and industry. His work spans the field of semiconductor nanostructures and semiconductor photonics. He has published more than 150 peer-reviewed research papers and edited/co-edited several books. He is associated with different international and national conferences in various roles and was general chair at FRCCD 2015 and ICCSE 2016. He is a reviewer for several journals as well as for several prestigious conferences in India and abroad.

Angsuman Sarkar, PhD, is Professor of Electronics and Communication Engineering at Kalyani Government Engineering College, West Bengal, India. He had earlier served at Jalpaiguri Government Engineering College and Kalyani Government Engineering College as lecturer, assistant professor, and associate professor. His research includes study of short channel effects of sub-100 nm MOSFETs and nanodevice modeling. He has authored books, book chapters, over 70 journal papers in international refereed journals, and many research papers in national and international conferences. He has delivered invited talks, tutorial speeches, and expert talks at international conferences and technical programs and has organized workshops and seminars as well as several IEEE international conferences.

Soumen Santra, PhD, is Assistant Professor in the Department of Master of Computer Application, Techno International New Town, Kolkata, India. He has 11 years of professional experience in academics and industry. His work is in the field of machine learning, the Internet of Things, and medical image analysis. He has published book chapters and more than 50 peer-reviewed research papers. He is associated with several international and national webinars in various aspects. He is a reviewer for several journals. He has achieved best mentor status of NPTEL online certification at his institute. He is working as a mentor and consultant for several industry-based projects and is also a faculty adviser of the Entrepreneurship Cell and Coding Trainer for the Placement Cell of the CA Department of Techno International New Town.

Table of Contents

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