federated learning

Lithium-ion battery health prediction under exhibit non-independent and identically distributed data: A systematic review of challenges and federated learning solutions

Threshold-grounded decision reliability for predictive maintenance under centralized and federated learning

This capsule supports independent verification of a threshold-grounded predictive-maintenance (PdM) reliability study. The work asks whether maintenance decisions remain defensible under a fixed operating threshold when industrial information is uncertain, class-imbalanced, and split across sites, comparing centralized...

AI in Predictive Healthcare II: A Ten-Domain Structured Evidence Review of Wearable Artificial Intelligence, 2024–2026

This expanded edition re-evaluates and extends a prior structured evidence review of artificial intelligence (AI) in wearable predictive healthcare. Where the original review verified evidence across four domains — atrial fibrillation, continuous glucose monitoring, federated learning and human digital twins — this edi...

A systematic review of AI powered adaptive smart home security using multimodal sensor fusion edge intelligence and privacy preserving architectures

Key findings reveal that current solutions remain fragmented across sensing, fusion, adaptation, and privacy dimensions, and that future research must prioritize unified frameworks jointly addressing multimodal fusion, continual adaptation, edge inference, privacy preservation, and explainability.

FairPFL

FairPFL is a federated learning framework for IoT intrusion detection that treats fairness as an operational requirement: no device population should be left systematically under-protected by the shared detector. It combines a self-correcting fairness controller in the aggregation rule, a split personalization architec...

Machine learning-based risk prediction models for type 2 diabetes in primary care: a scoping review

Evidence on ML-based risk prediction models for T2DM applicable to primary care remains limited despite growing interest in AI for diabetes prediction; greater emphasis is needed on external validation, calibration, prospective implementation, and evaluation across diverse primary care populations before widespread cli...

V5GIDS: An ETSI NFV MANO-Aligned Federated Intrusion Detection Framework for 5G Networks

Experimental results show that V5GIDS achieves strong detection performance in the evaluated settings while improving deployment relevance through orchestration alignment, reduced telemetry exchange, and resource-aware distributed operation.

Adaptive feature fusion based semi-supervised federated learning system for ECG arrhythmia detection

Automatic cardiac arrhythmia detection using electrocardiogram (ECG) signals is essential for early diagnosis of cardiovascular conditions. Most of the previously existing systems for arrhythmia detection depend on fully supervised learning approaches. In addition to that, since the ECG patient data is centrally stored...

[Global Livingry Governance Architecture | Part 12]: Autonomous Tsunami Early Warning and Emergency Response System Architecture: Integration of Community Camera Networks, Subsea Station UAVs, Security Systems, Edge AI, and Tensor Stress Index (TSI_{t+1})

Disaster management and mitigation in coastal regions and tectonic fault zones require a fundamental shift from manual, expert-committee-dependent response models to closed-loop automated architectures. By combining the Tensor Stress Index function (TSI_{t+1}), Edge AI processing, distributed community observation netw...

FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation

Gastric cancer is one of the most commonly diagnosed cancers and has a high mortality rate. Due to limited medical resources, developing machine learning models for image-based gastric cancer recognition provides an efficient solution for medical institutions. However, such models typically require large sample sizes,...

Grand challenge in microbiome data science: recovering the microbiome as a system

The microbiome has never been only a census of organisms. In its original ecological formula4on, the term described a microbial community embedded in a defined habitat, with its own physicochemical condi4ons and "theatre of ac4vity" [1; 2]. That original framing is useful now because it reminds us that microbes do not...

SECURE FEDERATED INTRUSION DETECTION USING HOMOMORPHIC ENCRYPTION: A COMPARATIVE STUDY WITH ENSEMBLE LEARNING

The rapid growth of the Internet of Things (IoT) has also resulted in the increase of the demand in the intrusion detection systems, which can detect suspicious activity and keep the information confidential. The traditional centralized machine learning systems involve attaching the data of the distributed devices to a...