We deployed an AI-based vision system integrated with the existing conveyor line. The system captures images of each carcass, analyzes quality parameters using deep learning algorithms, and displays real-time data on a centralized dashboard. It automatically counts carcasses, classifies them by quality grade, and generates business intelligence reports for management.

-Real-time image processing using artificial intelligence.
-Automated carcass counting and classification.
-Suspicious behavior monitoring.
-Centralized dashboard with analytics and reporting
-Multi-facility data aggregation

We implemented a vision system connected to existing RTSP cameras that analyzes the video stream in real time. The system detects each crate as it passes, identifies its size category, and updates counts instantly on the operator dashboard.

-Real-time video stream analysis from RTSP cameras.
-Detection and counting of full vs. empty containers.
-Size classification (small bucket, large bucket, empty).
-Live dashboard with production totals.
-Historical data logging for traceability.

We designed and manufactured a custom machine vision system that inspects every board as it exits the press. The system detects surface defects (scratches, cracks, discoloration) and precisely measures board diagonals to verify dimensional accuracy. Boards are automatically sorted based on defect severity.
Board width: 2440 mm - 2900 mm, Board length: 7320 mm - 8530 mm

-High-resolution line scan cameras.
-Real-time dimension measurement.
-Defect detection and classification.
-Automatic sorting based on quality grade.
-Integration with production line PLC.

We installed a high-resolution vision system on the production line that captures images of the steel sheet as it moves. Advanced image processing algorithms detect defects, classify them by type, and segment the affected areas for detailed analysis.

-High-resolution 5 MP camera with telecentric lens.
-Real-time defect detection and classification
-Defect area segmentation for detailed analysis.
-Custom user interface designed with PyQt5
-Local processing on NVIDIA Jetson Nano.

We deployed an AI vision solution that monitors defined zones in real time. The system detects workers entering restricted areas and checks each individual for proper PPE compliance. Alerts are generated instantly when violations occur.

-Person tracking in defined zones.
-PPE detection: helmets, glasses, vests, masks, safety shoes, ear protectors
-Real-time alerts and pop-up notifications
-User management with role-based access.
-Flexible camera addition and configuration.
-Zone configuration for customized monitoring areas.
-Login interface.
-Settings tab for system customization

We developed the IdealVision MiniLab—an automated inspection machine specifically designed for glass container geometry analysis. The system captures over 100 parameters per container, including dimensional measurements, symmetry, wall thickness, and surface characteristics. With support for multiple container shapes and sizes, the MiniLab delivers consistent, repeatable inspection results without manual intervention.

-Dual Modes.
-Recipe Management.
-Multi-Shape Support.
-Real-time inspection results displayed clearly.
-Generate reports for quality records or customer documentation.
-History Tracking.
-Diagnostic Screen.
-PLC Communication.
-Debug Log.
-Actuator Calibration.
-Login Levels.
-Intuitive Interface.