SRD AI

What SRD AI Does

SRD AI is developing a monitoring system for AI and computer-vision models deployed on edge devices. It helps detect when changing conditions, sensor issues, or data drift may be making an AI system less reliable—before unnoticed errors cause operational losses.

Why AI Becomes Less Reliable in the Field

Changing Conditions

Lighting, weather, dust, backgrounds, and operating conditions can differ from the data used to train the model.

Sensor Problems

Cameras and sensors can become dirty, blocked, damaged, misaligned, or affected by vibration and wear.

Data Drift

Real-world data can gradually change while the AI system continues operating without a clear warning.

How SRD AI Works

Monitor

Track signals from the AI model, sensors, environment, and operating conditions.

Detect

Identify patterns that may indicate increasing reliability risk or abnormal system behaviour.

Alert

Provide reliability indicators, affected locations, and recommended actions for operators or engineering teams.

Product Concept

A concept interface for monitoring AI reliability in real time and reviewing the factors affecting system performance.

Live Monitoring

View location-based reliability conditions, risk levels, and recommended actions in real time.

Reliability Analysis

Review the main factors affecting reliability and understand where inspection or intervention may be needed.

Currently Validating in Agriculture

SRD AI is currently learning from agriculture stakeholders, where cameras, sensors, smart sprayers, and AI-enabled equipment must operate under changing weather, dust, variable lighting, crop variation, and other difficult field conditions.

The goal is to understand where reliability monitoring can create measurable value for growers, equipment companies, technology providers, and engineering teams.

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