Case Study: Leading Rail Transportation Company achieves scalable real-time monitoring and preventative maintenance with Altoros

Enabling Monitoring and Preventative Maintenance for Railway Stations

A provider of transportation solutions — a division of a German-based conglomerate that supplies commuter, regional, high-speed and intercity trains, locomotives and metros — turned to Altoros after its legacy monitoring system failed to scale and deliver critical messages in time. The customer needed a scalable system to monitor railway crossings and equipment from multiple vendors, standardize heterogeneous protocols, and notify responsible parties in real time about accidents or dangerous situations.

Altoros implemented a microservices-based architecture with a custom application-level protocol, HiveMQ for real-time, prioritized notifications (critical, warning, informational), and TensorFlow-based video analysis for detecting hazardous situations, plus Apache Kafka for secure policy handling. The solution now aggregates petabytes of data per day with megabytes-per-second throughput, compresses messages to cut internet costs, delivers real-time critical alerts, enables preventative maintenance via a unified dashboard, and has created an additional revenue channel for the customer.