Automation World

The Insight-to-Action Gap: How Integrating ML Anomaly Detection with CMMS Eliminated 84% of Unplanned Downtime

Predictive maintenance fails not from bad models, but broken handoffs. Here's the integration architecture that closed the ...
Market.us Scoop

Anomaly Detection Market Towards US$ 33.32 Billion by 2035

Anomaly Detection Market is predicted to register growth from USD 5.61 bn in 2025 to about USD 33.32 bn by 2035, recording a ...
pv magazine USA

All emerging cyber threats targeting power infrastructure at a glance

Researchers in Morocco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense strategies against threats like distributed denial-of-service, false data ...
IEEE

Anomaly Detection Method Based on Dynamic Graph Structure and Multi-Modal Fusion for IoT

Abstract: In the era of increasingly complex and covert network attack on Internet of Things (IoT), existing anomaly detection paradigms often exhibit limitations in characterizing the dynamic ...
Scientific Research Publishing

Prototype-Based Dynamic Autoencoders for Real-Time Anomaly Detection and Explainability ()

Real-time detection of anomalies in data streams is a foundation of modern applied analysis in complex systems. It enables experts to design rapid, efficient, reliable, and high-performance decision ...
Scientific Research Publishing

Sandhu, K., Reddy Bojja, S.G., Venkataramanan, S. and Reddy Vangoor, V.K. (2024) AI-Powered Anomaly Detection in Zero Trust Environments: A Comprehensive Review of Methods and ...

ABSTRACT: The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior using deep learning methods and ensuring interpretability of ...