Computing and Communications Engineering in Real-Time Application Development

ISBN-13: 9781774638361 / Angielski / Twarda / 2022 / 284 str.

Opis

Focuses specifically on real-time applications in electronics, communications, computing, and information technology. Topics address applications for automotive use, detecting DoS attacks, social media and consumer applications, and hostel management, firefighting, and heart rate variability for predicting cardiac health.

Spis treści

1. Smart Car Parking System Using IoT and Cloud Technology  2. Design and Development of Motor Speed Controller Using Brushless Direct Current Hub Motor for Electric Two-Wheelers  3. Design and Implementation of Fair FARE System Using IoT for a Public Transport System  4. Haze Mitigation and Visibility Restoration in Foggy Conditions for Vehicles  5. A Comprehensive Study of and Possible Solutions for a Hostel Management System  6. Fire Fighting Robot Using GUI and RF Technology  7. Detecting DOS Attacks by Considering Energy Consumption Based on Traditional Monitoring Charts and Proposed Parameters  8. Multiscale Rotation Invariant Local Features Extraction for Hyperspectral Image Classification Using CNN  9. Sentiment Analysis of Twitter Data Using Named Entity Recognition  10. Visual Cryptographic Approach for Authentication of Social Media Contents  11. Comparative Analysis of Clustering Algorithms  12. IoT-Enabled Smart Container  13. Quantum Computing to Enhance Performance of Machine Learning Algorithms  14. Review of Lightweight Cryptography for Secure Data Transmission in Resource Constraint Environment of IoT  15. Robust Reversible Watermarking Using Binary XORed  16. Telecom Customer Churn  17. Implementing a Web Application to Provide Personalized Preliminary Treatment for Diabetes Based on History  18. Marine Trash Detection Using Deep Learning Models  19. Enhancing Session-Hijacking Attack Using Session Security on a Browser with Disposable Credentials Using OTC  20. Grayscale Image Colorization Using Deep Learning: A Case Study  21. Heart Rate Variability Analysis and Machine Learning for Prediction of Cardiac Health