Full Description
This book presents selected papers from International Conference on Sustainable Computing and Intelligent Systems (SCIS 2025), held on 7-8 November 2025, in University of Canberra, Bruce, Australia. The topics covered in the book are green computing, renewable energy integration, sustainable urban computing, IoT and sustainability, sustainable IoT applications, data analytics for sustainability, internet of things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, intelligent IoT eHealth, bio-inspired intelligence, brain modeling and simulation, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, hybrid systems and intelligence for security.
Contents
Data-Driven Sustainability in Supply Chains: A Review of Analytics for Carbon Footprint Reduction.- Minimizing Return Rates in Online Fashion through Personalized Avatar-based Fitting.- A Comprehensive Analysis on WLAN MAC Layer Speed Estimation using ML based Predictors.- A Lightweight Prototype-Augmented Segmentation Network with Ablation study and Efficiency Analysis.- Energy-Efficient Cloud Computing for Carbon Footprint Reduction: A Scientometric Analysis.- GAN-Enhanced Hybrid Models for Paddy Leaf Disease Detection: Review, Challenges, and Solution Framework.- Beyond the Books: Understanding Student Stress in Modern Education.- Adaptive Waste Collection Routing in Smart Cities using Multi-Agent Systems.- Modified BIRCH-Based Hierarchical Clustering for Color Image Segmentation.- WanderSnap: A Multimodal AI Framework for Personalized and Adaptive Travel Itinerary Generation.- SynergyGrid: An Optimised Embedded IoT Architecture for Sustainable Power Monitoring and Industrial Applications.- MetPhaFrac: Detection of Metacarpophalangeal Fractures using Mask R-CNN Inception v3: An AI-driven Approach.- Decision Flow Tracing and Word Impact Analysis in Hybrid Transformer-Conditioned Diffusion Models for Text-to-Image Generation.- BFS-Net: A Bi-level Feature Selection Network for Fine Grained Sketch-Based Image Retrieval.- Improving Echocardiographic Image Quality through Hybrid Contrast Enhancement using DHE and GAN.
