Discover how UNX Digital is transforming the monitoring of train formations at stations using computer vision. This innovative solution improves operational efficiency, safety, and passenger experience, all while remaining cost-effective and easy to implement.

Hardware: Jetson Nano + Azure Cloud Services
Application: Real-time frequency of arrivals and departures of train formations
Industry: Transportation
Deployment Location: Argentina

Background: Uncovering the Opportunity

In the realm of railway operations, efficient monitoring of train formations is crucial for maintaining a precise schedule and ensuring passenger safety. However, manual monitoring of formations can be a challenging and error-prone task, especially in stations with high traffic volume.

Challenge: The Efficiency Challenge

The task was to detect the frequency of arrivals and departures of train formations at different stations, using video ingestion and computer vision. Manual monitoring was not only inefficient but could also lead to errors that could have serious consequences.

Solution: Innovation in Action

To tackle this challenge, Artificial Intelligence models were incorporated that use the existing camera infrastructure to identify plates. By applying Computer Vision to video ingestion, markers that make patent plates could be detected, allowing for the collection and processing of the obtained data. This solution allowed for more efficient and accurate monitoring of train formations, improving safety and operational efficiency. In addition, the implementation and rollout of the solution proved to be simple and economical compared to other potential solutions, such as the use of industrial RFID tags per formation.

Business Impact: Transformative Outcomes

With the implementation of this solution, train stations were able to significantly improve the efficiency of their train formation monitoring. This not only improved safety but also allowed for better management of train schedules, which in turn led to a better experience for passengers. Furthermore, the ease and economy of the solution’s implementation resulted in a quick and significant return on investment for the stations.