Smart Technologies and Intelligent Computing

Jaskaran Singh, Meenu Gupta, Rakesh Kumar

• Publisher: CRC Press
• Year: 2026
• eBook ISBN: 9781040885734
• Topic: Computer Science
• Subtopic: Computer Engineering
• Index: Computer Science

This book compiles the proceedings of the International Conference on Smart Technologies and Intelligent Computing (INCSTIC 2025), organized by the School of Computer Science and Engineering, Geeta University, Panipat, Haryana, India.

It brings together innovative insights and practical solutions in diverse domains such as Smart Technologies, Intelligent Computing, Artificial Intelligence, Machine Learning, Internet of Things (IoT), Cloud Computing, Big Data Analytics, Advanced Networking Solutions, System Design and Methodologies, and ICT for Sustainability. With novel approaches and real-world applications, this collection of peer-reviewed papers aims to address emerging challenges in smart and intelligent systems.

This volume serves as a valuable resource for researchers, academicians, industry professionals, and students in the fields of Computer Science, Artificial Intelligence, Smart Systems, and Multidisciplinary Technologies. It aims to inspire collaboration and knowledge exchange among academia and industry, fostering innovation that drives the future of sustainable computing.

Table of contents

• Cover
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgements
• Editor biographies
• Advisory Committee
• Organizing committee
• Optimizing text classification: Particle swarm approach to random forests
• Deep learning approaches for reliable object detection under adverse weather
• IoT-based water pipeline leakage detection system
• Handwritten examination evaluation using LLMs and GenAI
• Deep retinex-inspired enhancement of low-light lunar images using dark-bright image pairs
• Solar irradiation component forecasting using ANN framework with diverse configuration of meteorological parameters
• Quantum-enhanced machine learning for predictive catalysis: A unified framework for transition metal complex activity forecasting
• Voice-based Parkinson’s disease prediction using machine learning
• Artificial Intelligence for hand gesture to speech conversion
• Predictive modeling for cervical cancer detection using machine learning
• A hybrid CNN-transformer model for multi-marker detection in cerebrovascular disease using multimodal imaging
• Advancing lung cancer prediction: A comparative study of ML, DL & hybrid models
• Enhancement in HTM-CLA for credit card fraud detection using H-DS and H-MSC classifier
• Multi-model learning system using EfficientNet classifier for malnutrition management
• AI-driven healthcare management system
• Handwritten digit recognition using deep learning
• Real time trespassing detection using YOLOv5 and ONXX deployed through a streamlit web application
• AWS-enabled centralized bus booking system: A scalable and efficient cloud-based solution
• Common salts classification using Raman spectroscopy and deep learning
• Well mind: AI-powered mental health monitoring and prediction
• DeepFrontal: Deep learning-based 3D face reconstruction from 2D views
• YOLOv11-based emergency vehicle detection
• Deep learning-based facial emotion recognition system
• Hybrid-DS-SCNet: Lightweight module for facial emotion detection
• Fine-tuned transformer models with explainability for Android malware detection
• Evaluating feature importance in AI-driven crop water stress models
• Screening of pulmonary embolism using large language model
• Enhanced cloud service ranking using a hybrid RoBERTa-based deep learning framework with multi-criteria decision support
• Deep ensemble framework for robust classification of pulmonary diseases from radiographs
• Optimized serverless cloud-based real-time processing architecture for sensor data analytics in healthcare
• Crop yield stack: A multi-model ensemble approach for enhanced agriculture forecasting
• Investigating long-term impact through AI insights and 5g innovation integration
• GenAI for automated medical reports: A retrieval-augmented framework
• GRFAT-MH: A privacy-preserving AI Tutor for mental health support in rural classrooms
• Machine learning-based land-use and land-cover classification using Google Earth Engine over a part of Haryana, India
• Comparative analysis for calorie burn prediction using machine learning techniques
• Deep learning for brain tumor segmentation-comparison of architectures & activation functions
• Hardware-software co-design for energy efficient machine learning on FPGA
• Real-time plant disease identification via CNN-based leaf image classification and mobile deployment
• Hybrid deep learning approach for brain tumor detection using ResNet and EfficientNet
• FoodScanAI: A dual-modal deep learning system for food spoilage detection using synthetic sensor data and image classification
• Y-PN-MSSD-based yogic meditation for psycho-oncology subject with kyphosis
• Hybrid deep-cuckoo framework for robust brain tumor detection and segmentation in MRI scans
• A real-time forest fire detection and alert system using deep learning and satellite imagery
• Optimized hybrid machine learning techniques for predictive analysis of lung cancer
• Machine learning-based prediction and recommendation system for anxiety and depression
• Early identification of Alzheimer’s disease: Leveraging support vector machines for predictive insights
• Privacy-preserving techniques in data anonymization and masking: Trends and challenges
• An efficient edge-based segmentation model with correlation weighted linked feature vector for melanoma detection using VGG16
• Detection of epileptic seizures in EEG signals: Analysis of linear time-domain features using classical machine learning techniques
• Early diagnosis and detection of Parkinson’s disease using AI
• IoT-enhanced vehicle monitoring solution with intuitive mobile application for AI-based Android and iOS devices
• A novel framework for improving cloud IoT efficiency with virtualized networks
• Transformer-based deep learning approach for channel estimation in MIMO wireless systems
• Leveraging VGG19 for accurate detection of apple plant diseases
• Energy efficient data aggregation and adaptive compression model with reduced loss levels in wireless sensor networks
• Low-cost wireless EMG-controlled prosthetic arm using 3D printing
• Comparative analysis of legal text summarization using transformer-based models
• Blockchain for ethical AI model Validation
• Lw-CovidNet: Lightweight deep-learning module for disease prediction in CT scan images
• Intelligent mental health monitoring in the workplace: A deep learning perspective
• Novel seismic neural network approach for robust intrusion detection using texture-based features
• AI-driven big data analytics: Unveiling insights for next-gen intelligent systems
• A hybrid neuro-fusion model for network intrusion detection using non-symmetric deep autoencoders and transformer-augmented gradient boosting
• Zero- and few-shot Arabic text summarization using retrieval-augmented generation
• Smart beekeeping monitoring system using IoT and machine learning
• SoilSense: Soil quality prediction using real-time LSTM-GNN
• Silent video to text: CNN-based deep learning model for lip movement recognition and transcription
• Explainable deep learning models for ECG classification using CNN, LSTM, and BiLSTM architectures
• Early breast cancer detection using integrated feature selection and quad-learner ensemble based hunting–tracking optimization
• Deep learning CNN model-based stock price prediction by candle stick images
• Class imbalance handling and metaheuristic optimization of XGBoost for breast cancer detection
• Quantum-secure authentication and robust retrieval for remote sensing
• A reduced analytical review of intelligent IoT security: Trends, gaps, and future challenges
• Deep learning-based road damage detection and severity assessment using explainable AI
• Neural architecture search for real-time object detection in drone navigation
• Advancing patient outcomes in Indian healthcare through AI-enabled diagnostic and communication systems
• Artificial Intelligence and Blockchain-enabled privacy in assistive technologies for disability empowerment
• Deep neural networks for the diagnosis of Parkinson’s disease through visual feature learning
• Hybrid attention network with TabNet benchmarking for breast cancer and heart disease classification
• Log Gabor and wavelet-based transform for enhanced CT MRI image fusion
• Assessing risks to children’s privacy in smart toys within intelligent communication systems
• Smart technologies and intelligent computing for AI-driven gesture recognition in rehabilitation, yoga, and learning
• Bias detection and mitigation in large language models: A fairness-driven approach
• Context-aware local querying model using Llama 3 and DeepSeek R1
• Meta-modeling for cardiovascular risk prediction
• AI-driven models for accountability and transparency in public sector administration
• Evaluating the effectiveness of advanced LSTM variants in weather forecasting prediction models
• Leveraging AI for intelligent decision-making in space mission planning
• A hybrid CNN–transformer framework with self-supervised and federated learning for privacy-preserving cardiovascular disease diagnosis
• A unified ontology-based and semantic interoperability framework for smart agriculture systems
• Human-in-the-loop: A hybrid orchestration model for intelligent automation
• Multiclass brain tumor classification using vision transformer
• AI-powered customer support chatbot leveraging feedforward neural network architecture
• Quantum-inspired federated learning framework for real time IoT cybersecurity
• Cyberbullying detection through image classification: D-Net architecture
• Optimized YOLO model to control traffic flow dynamically by analysing traffic density and conditions
• Sentiment analysis on social networking data using NLP and deep learning
• AI-driven IoT framework for smart health monitoring using embedded sensors and edge analytics
• Tomato leaf disease detection and classification using CNN with Grad-CAM
• Deep feature fusion and hybrid CNN-SVM architecture for reliable and explainable drug toxicity prediction
• Author index