MicroEDS 2025 A Cutting-Edge Machine Learning Solution for Industrial Event Detection.

Advanced Detection Algorithms*

• Subtle Anomalies
• Data Quality Filtering
• Trend & Pattern Recognition
• Adaptive Thresholds
• Rule Violations
• Sensor Noise Analysis
• I/ODiagnostics
• Event Correlation
• Hazard Signature Matching

Type A –Server-Based Deployment

Installation on a dedicated server or cloud infrastructure for centralized processing and scalability.

Stay Ahead with Intelligent Monitoring

Managing critical equipment and processes requires real-time monitoring and advanced anomaly detection. MicroEDS proactively identifies potential issues before they escalate, eliminating the need for complex and costly data analysis upfront.

MicroEDS is a flexible and scalable System designed to integrate seamlessly with your existing infrastructure, supporting multiple deployment options.

Type B – Edge Computing (SDCard-Based)

Run MicroEDS directly on Single- Board Computers (SBCs) like Raspberry Pi for efficient, localised event detection without heavy infrastructure.

Type C -Containerized Solution (Docker Based)

Deploy MicroEDS in a Docker container on Windows or Linux for a lightweight, portable, and easily maintainable setup.

With these configuration, MicroEDS delivers real-time anomaly detection wherever you need it.

Main features of MicroEDS

• Complete Modbus/TCP integration, MicroEDS reads sensor data at ultra-fast 100-millisecond intervals
• Seamless & Fast Installation
• Intelligent False Alarm Filtering
• Standalone & Industry-Ready Using standard protocols
• Advanced Machine Learning Models
• Adaptive Monitoring
• Customisable Sensitivity & Event Classification
• Remote & Secure Access
• Cloud Backup & Data Security

More of our services

• Historical Data Analysis: Uncover trends and insights from past data.
• Hazardous Event Classification: Identify and categorise historical events.
• Monitoring Station Performance Evaluation: Assess the efficiency and accuracy of monitoring.
• Periodic Model Calibration: Ensure ongoing accuracy with regular calibration
• of online detection models.
• Secure Remote Monitoring: Monitor field devices remotely through a
• secured communication network.

* About our advanced detection algorithms

MicroEDS leverages powerful machine learning algorithms for real-time anomaly detection, identifying potential issues before they escalate. Key detection methods include:

•Adaptive Thresholds – Detecting deviations from expected statistical limits.

•Subtle Anomalies – Identifying irregular fluctuations that hint at emerging issues.

•Rule Violations – Flagging inconsistencies based on predefined operational parameters.

•Pattern Recognition – Monitoring long-term trends to prevent gradual failures.

•Data Quality Filtering – Eliminating static values and excessive noise.

•I/O Diagnostics – Detecting abnormal hardware behavior.

•Event Correlation – Recognizing unusual sensor data combinations.

•Hazard Detection – Identifying potentially dangerous parameter alignments.

•Sensor Noise Analysis – Evaluating inconsistencies across sensor groups.

•Signature Matching – Comparing data patterns to known risk indicators.

With these intelligent detection capabilities, MicroEDS helps industries prevent failures, optimize operations, and improve system reliability.