Detect maritime anomalies from AIS data
MVTec website
Monitor and analyze ADAS sensor data
Identify and visualize anomalies in Excel data
Detect anomalies in images
Implement using models like Isolation Forest/Local Outlier.
Detect anomalies in Excel data
Detect anomalies in images
Detect fraudulent Ethereum transactions
A powerful AI-driven anomaly detection AP
Detect anomalies in time series data
Identify image anomalies by generating heatmaps and scores
Classify images as normal or anomaly
NavAI Guard is an AI-powered anomaly detection solution designed to identify maritime anomalies from AIS (Automatic Identification System) data. It leverages advanced machine learning algorithms to monitor and analyze vessel movements, ensuring real-time detection of unusual patterns that may indicate potential threats or irregular activities.
• Real-time Anomaly Detection: Continuously monitors AIS data to detect deviations from normal vessel behavior. • Customizable Alerts: Set specific thresholds and parameters to trigger alerts for suspicious activities. • Advanced AI Engine: Utilizes sophisticated algorithms to identify complex patterns and anomalies. • Historical Analysis: Provides insights into past anomalies for forensic investigations. • Integration Capabilities: Seamlessly integrates with existing maritime surveillance systems. • User-Friendly Interface: Offers an intuitive dashboard for easy monitoring and management.
What types of anomalies can NavAI Guard detect?
NavAI Guard can detect a wide range of anomalies, including unusual vessel routes, unexpected stops, loitering, and suspicious proximity to restricted areas.
How accurate is NavAI Guard in detecting anomalies?
NavAI Guard leverages advanced AI algorithms to achieve high accuracy in anomaly detection. However, accuracy can be further improved by fine-tuning the system with specific operational data.
Can NavAI Guard integrate with existing maritime systems?
Yes, NavAI Guard is designed to integrate seamlessly with most maritime surveillance systems, allowing for a smooth and efficient deployment process.