federated learning

INTEGRATING ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN TECHNOLOGY INTO SMART MOBILE APPLICATIONS

The rapid development of contemporary technologies tends to digitalize all services across various public and private institutions, where most services are also provided on mobile devices due to their great practical usability by people in everyday life. The integration of Blockchain Technology (BT) and Artificial Inte...

Federated Learning and Blockchain Integration for Privacy-Preserving Smart Classrooms

The development of smart classroom technology hastened the implementation of data-driven and personalized learning systems, with the significant concern of data privacy, security, and trust. In this chapter, the author introduces a combined system of Federated Learning (FL) and blockchain to implement decentralized and...

Artificial intelligence, explainable deep learning, and generative models for osteoporosis and bone disease prediction: a systematic review and future research roadmap

Osteoporosis is a major global health burden, with considerable morbidity, mortality, and healthcare costs. Artificial intelligence (AI) has opened new avenues for osteoporosis screening, bone mineral density quantification, fracture-risk prediction, and clinical decision support, but progress remains fragmented across...

Sustainability intelligence: Integrating Artificial Intelligence, the Internet of Things, and Digital Twins for resource-efficient and climate-resilient systems

Sustainability has become one of the defining scientific and societal challenges of the twenty-first century. Climate change, rapid urbanization, population growth, increasing energy demand, and declining natural resources require decision-making that is continuous, adaptive, and supported by reliable environmental int...

AI-Driven Personalization and Adaptive Learning in Decentralized Environments

With the rapid growth of digital technologies, the traditional education system is transforming into intelligent and decentralized learning environments that support personalized and adaptive learning experiences. Conventional educational platforms often face challenges such as scalability, learner engagement, data own...

Fair Bayesian Stackelberg Federated Learning Under Strategic and Heterogeneous Client Participation

Federated learning must accommodate statistical heterogeneity, costly client participation, and distinct fairness objectives for model performance and participation frequency. We introduce Fair Bayesian Stackelberg Federated Learning (FBS-FL), in which a server maintains beliefs over private client cost types and selec...

FedStaP: Shared Feature Statistics and Prior-Calibrated Training for Non-IID Federated Intrusion Detection in IoT Networks

Federated learning allows IoT gateways to train a shared intrusion detector without exporting traffic records, but gateways observe different attack classes and scale their flow features differently. Stateful optimisers such as SCAFFOLD correct the resulting client drift at the cost of per-client memory and twice the p...

P146: Federated analytics across heterogeneous stores: Cross-cloud comparative study

Federated analytics across heterogeneous stores: Cross-cloud comparative study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud data platforms are no longer used o...

Web4 and Autonomous AI Agents in Decentralised Education Ecosystems Transforming Intelligent and Personalized Learning

The rapid emergence of Web4 technologies, autonomous AI agents, blockchain systems, and immersive virtual environments is redefining the future of education. Decentralized education ecosystems are enabling intelligent, learner-centric, secure, and adaptive educational experiences beyond traditional digital learning mod...

BlockGuard: Serverless Selective Homomorphic Encryption for Federated Learning

Introduction to Computational Analysis in Medical Imaging

The exponential growth of digital imaging modalities like CT, MRI, Ultrasound, PET and digital pathology has produced huge amount of high dimensional data. This data having powerful insights need advanced computational techniques for accurate interpretation and clinical decision making. In the clinical setting, sophist...

Blockchain Federated Learning Architecture

Customizing education technology with data-driven AI undermines student privacy. Centralized analytics risk illegal data access, single points of failure, and loss of institutional sovereignty. BFL-EdArch, a four-layer blockchain-enabled federated learning architecture, enables privacy-preserving collaborative intellig...