Product
The product is the RailEyes Smart Camera and Analytics suite. It consists of a proprietary, robust "Smart Camera" (hardware) designed to be mounted on existing trains and an "AI-powered inspection suite" (software) that analyzes the video feed.

Sector
The product targets the Railway industry 🚂, specifically for rail infrastructure managers and operators responsible for network maintenance, safety, and operational efficiency.

Use Case
The primary use case is automated, real-time railway infrastructure monitoring and inspection, replacing costly, inefficient, and environmentally harmful manual methods.

The main focus is advanced vegetation management. The system automatically identifies and provides actionable insights on:

Catenary Obstruction: Trees and branches growing too close to overhead power lines.

Ground Instability: Grass growing on the track bed, which can signal drainage or stability problems.

Secondary use cases include automated detection of:

Dangerous objects on the track

Human or animal presence

Signal recognition and equipment condition

Crowd volume at stations

Technology
The solution's technology is broken down into hardware and the specific AI software components:

Hardware (Smart Camera)
The camera is a "powerful edge device" specifically engineered for trains. It is heat-resistant, customizable, and includes:

Connectivity: GPS, Wi-Fi, and mobile network capabilities for real-time data transfer and location tracking.

Storage: Onboard storage to ensure continuous recording, even in areas without network coverage.

Security: Encryption to protect recorded data.

Software (AI & Analytics)
The system uses several key AI-driven software features:

Monoscopic Depth Estimation: This is a core AI algorithm that analyzes a single 2D camera image to accurately estimate the distance of vegetation from the track. This specifically eliminates the need for more expensive hardware like LiDAR or radar.

Vegetation Detection: An AI pipeline classifies different types of vegetation (e.g., trees, grass) to provide targeted maintenance recommendations.

Track-based Zoning: The software digitally splits the camera's view into distinct zones relative to the track, allowing for different detection rules in each area.

Real-time Anonymization: To comply with EU privacy laws, the system automatically blurs faces and other identifiable information in the video feed.

Web Application: A platform where operators can search, view, and download video clips filterable by track kilometer, station, or track ID.