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Automated Raiway lines Inspection

The AI-RWay project aims to create an innovative platform designed to automate and optimize the maintenance of railway infrastructure by leveraging drones, artificial intelligence, and advanced image analysis.

The system enables the automated inspection of railway lines, by detecting obstacles, anomalies, and invasive vegetation, as well as monitoring the condition of signaling equipment.

As a partner, Zirak contributes to the design of the software architecture, data pre-processing and management, as well as the selection and integration of AI and Computer Vision models. The platform provides end-to-end monitoring, scheduling of interventions, and historical data management, ensuring timely and traceable actions.

The project also includes demonstrations in real-world scenarios to validate the solution under diverse operational conditions.

Project details ->

Virtual sensors

Application of various Machine Learning models and algorithms to estimate the rotor temperature and torque of a Permanent Magnet Synchronous Motor (PMSM) through the implementation of virtual sensors.
Objective: to support automotive industry manufacturers in optimizing raw material usage during motor production and enabling strategies for utilizing the motor to its maximum potential.
The result achieved was a high level of prediction accuracy and strong reliability in early problem detection, supported by field data.

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