Emerging Perspectives and Applications of Computational Intelligence and Smart Systems

Amit Lathigara, Nirav Bhatt, Paresh Tanna

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040820506
• Topic: Computer Science
• Subtopic: Robotics
• Index: Computer Science

Emerging Perspectives and Applications of Computational Intelligence and Smart Systems delves into the transformative role of artificial intelligence, machine learning, IoT, robotics, smart technologies etc. in shaping the future of industries and societies. This volume presents cutting-edge research and real-world applications that highlight how computational intelligence enables automation, intelligent decision-making, and sustainable solutions across diverse domains. With contributions from experts in academia and industry, the book explores innovations in healthcare, smart cities, energy systems, manufacturing, and beyond. It emphasizes interdisciplinary collaboration and practical methodologies that bridge the gap between theoretical advancements and tangible impact. By combining theoretical advancements with real-world relevance, this book equips readers with a deeper understanding of how intelligent technologies can be applied to solve complex problems. It is an essential guide for those looking to harness computational intelligence and smart systems to drive innovation, improve efficiency, and contribute to a more sustainable and connected future.

Table of contents

• Cover Page
• Half Title Page
• Title Page
• Copyright Page
• Contents
• List of Figures
• List of Tables
• Acknowledgements
• About the Editors
• 1 Investigating an Updraft Coal Gasifier Using Advanced Hot Gas Cleaning Technology Through Experimentation to Reduce Pollution for Sustainable Development
• 2 AI-Driven Skin Type Detection and Personalized Recommendations for Cosmetic Products
• 3 Lung Cancer Stage Detection Using CNN: A Review
• 4 IoT and RFID-Enabled Smart Lab Monitoring System for Efficient Asset Management
• 5 Detecting System Vulnerability to Malware Attacks Using ML Techniques: A Review
• 6 A Systematic Review on License Plate Recognition using Deep Learning
• 7 Hybridizing ML with CatBoost and LightGBM for Liver Disease Prediction: An Improved Clinical Data Analysis
• 8 Enhancing IoT Security: A Hybrid Deep Learning Approach for Network Traffic Classification
• 9 Enhanced Motion Control for PMSM Using Direct Torque Control Algorithm
• 10 Student Performance Prediction in Introductory Programming Courses: A Comprehensive Review of Machine Learning Techniques
• 11 Real-Time Traffic Monitoring and Request Blocking Firewall for Network Security
• 12 Strategies for the Advancement of Artificial Intelligence (AI) Technologies and Their Application in Intelligence and Counter-Intelligence Operations (The Experiences of the United States and China)
• 13 Comparative Performance of Machine Learning Algorithms for Sentiment Analysis: The Role of PCA as a Dimension Reduction Technique
• 14 Machine Learning-Based Attack Detection in Smart Home IoT Networks
• 15 Development of Knee Joint Implant using VAT Polymerization and Investment Casting
• 16 A Comparative Review of a Single-Stage and Two-Stage Grid-Connected PV Systems
• 17 Advancements in Automatic Load Frequency Control with Integration of Renewable Energy Sources: A Comprehensive Review
• 18 A Feasibility Study on The Use of Los Angeles Machine to Grind Fly Ash
• 19 Effective Analysis of Mental Health Using AI and Machine Learning in Social Media Analytics
• 20 Enhancing Multi-Modal MRI Brain Tumor Detection using Hybrid Convolutional Based Deep Learning Model
• 21 Real-Time Adaptive Decision-Making in Unstructured Agricultural Scenarios Based on WSN and Deep Learning
• 22 Assessing Global Water Scarcity Using the WEAP Model: Implications for Sustainable Development
• 23 IoT-Driven Batch Tracking System for Pharmaceutical Quality and Compliance in Industry 4.0
• 24 AI-Driven Load Balancing in Cloud Computing: A Deep Reinforcement Learning Approach
• 25 A Comprehensive Review of Intrusion Detection in In-Vehicle Networks: Advances, Challenges, and Insights from the CICIoV2024 Dataset
• 26 Improving Educational Outcomes with AI: Predicting CGPA Using Socio-Economic Factors
• 27 Transformer-Based Deep Learning for Stock Price Prediction: The Impact of Sentiment Analysis
• 28 Optimization of Tractor Seat Suspension for Vibration Reduction Using MATLAB-Based Transmissibility Analysis
• 29 AI-Enhanced Energy Management Solutions for Smart Micro-grid Organism
• 30 Block Chain Based Smart and Secure Logistic Management System using AI
• 31 A Systematic Review of Intrusion Detection in IoT: Efficiency, Transparency, and Zero-Day Resilience
• 32 Real-Time Intrusion Detection and Cloud-based Facial Recognition for Smart Home Security Systems
• 33 Analysing Caloric and Mineral Intake from Fruit Consumption: A Computational Framework Using AI, IoT, and Machine Learning with Real-Time Wearable Output
• 34 Performance of ARIMA in TEC Prediction for Quiet and Disturbed Days Over the Equatorial Low Latitude Region
• 35 Dengue Detection using Machine Learning Approach
• 36 Leveraging Machine Learning Techniques for Predicting Major Diseases in Groundnut Crop Cultivation
• 37 Technological Advancements in Indian Policing: The Role of Digital Arrests
• 38 Enhancing Criminal Identification through Siamese CNN Facial Recognition: A Law Enforcement Perspective
• 39 Enhancing Organizational Security and Efficiency: A Digital QR Code-Based Access Control System
• 40 Optimizing MANET Routing with SINTM: A Smarter Load Balancing Approach
• 41 Networks Design and Evaluation of a Zone-Based Energy-Efficient Routing Protocol for Hybrid Wireless Networks
• 42 Enhancing Medication Adherence through an IoT-Enabled Automated Pill Dispenser with Real-Time Monitoring
• 43 Application of a Genetic Algorithm in 0–1 Knapsack Problem
• 44 An Extensive Analysis of a Deep Learning-Based Plant Disease Identification System
• 45 Exploratory Data Analysis and Feature Correlation Insights on the CICIoV2024 Dataset for IoV Security
• 46 Reinforcement Learning for 5G D2D Communication in Proximity-Based Networks
• 47 Deep Neural Network-Based Trust Management System with Enhanced Attack Resistance
• 48 Revolutionizing Cricket Team Selection: AI and ML-Driven Player Performance Prediction—A Comprehensive Review
• 49 Using Big Data Analytics in Wireless Cellular Networks: A Transformational Impact on the Telecommunications Industry
• 50 Forest Fire Prediction System using Wireless Sensor Networks and Deep Learning
• 51 Concept of Sliding Block Type Self-Centering Vise Clamp for Smart Manufacturing
• 52 Optimized Federated Learning for Decentralized Healthcare Data
• 53 Revolutionizing Cloud Computing: Decentralized Scheduling with Federated Learning for Enhanced Resource Utilization
• 54 Predicting Climate Change Impact on Crop Yield: A Review of AI-Based Implementations in Maharashtra *
• 55 Comprehensive Investigation of Cutting Parameters for “Nanowhite Crystallized Glass” Tiles
• 56 Optimized EEG-EMG Fusion Model for Continuous Hand Trajectory Estimation in Brain Computer Interfaces
• 57 Transformer and Graph Analytics for Big Data-Driven Intrusion Detection: A Novel Framework
• 58 Machine Learning-Based Crop Classification Using Random Forest for Precision Agriculture
• 59 Vibrating Massage Belt for Elderly and Working Women
• 60 Machine Learning for Sports Score and Winner Prediction: A Critical Review of Research Gaps and Model Enhancements
• 61 Enhancing Cybersecurity Resilience in 6G Networks Using Adversarial Machine Learning
• 62 Optimization of Steam Venting Loss in Coal-Fired AFBC Boiler by Controlling Coal Feeding Primary Air Lines Choking Issue
• 63 Real-Time IoT Solution for Smart Agriculture using Thingspeak and Whatsapp
• 64 Behavioral Analysis of QUIC Protocol under DDoS
• 65 Confidential AI Prompt Sharing: A Block-chain Driven Framework for Secure Data Exchange
• 66 Load Balancing Algorithm for Data Centers to Optimize Cloud Computing Applications
• 67 Food Calory Estimation and BMI Prediction using Ml
• 68 IoT Based Theft Detection using SMTP Protocol
• 69 The Impact of Oversampling Methods on Predicting Employee Turnover