A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.
Author(s): Shabir A. Parah; Nasir N. Hurrah; Ekram Khan
Publisher: Springer International Publishing
Year: 2023
Language: English
Pages: 372
Cover
Front Matter
Part I. Smart Ecosystems: Opportunities and Challenges
Smart Ecosystems for Sustainable Development: Opportunities, Challenges, and Solutions
Big Data in Smart Ecosystems: Trends, Challenges and Future Prospectus
Breakthroughs and Challenges in Multimedia Privacy and Security in the Internet of Things (IoT)
Analysis of Ensemble Methods for Phishing Detection
Part II. Intelligent Signal Processing for Smart Health
Machine Learning Based Diabetic Retinopathy Detection and Classification
CNN-SVM with Data Augmentation for Robust Blur Detection of Digital Breast Tomosynthesis Images
Lung Lesion Identification Using Geometrical Feature and Optical Flow Method from Computed Tomography Scan Images
Performance Improvement with Optimization Algorithm in Isolating Left Ventricle and Non-Left Ventricle Cardiac
Dual-Feature CNN-SVM Method for Breast Mass Tissue Abnormality Classification on Digital Mammography Images Adapted to Breast Density
Deterministic SEIR Mathematical Model for Infectious Diseases Like COVID-19
Part III. Intelligent Signal Processing for Smart Industry
Detection of Power Distribution Fault in Thermal Images Using CNN
Text to Speech Synthesis Using Deep Learning
Advanced Sequence Learning Approaches for Emotion Recognition Using Speech Signals
Comparison of Deep Learning Model Performance for Handwritten Character Recognition of Schoolchildren
Handwritten Urdu Recognition Using BERT with Vision Transformers
