Transform Railway Operations using AI
SYNAP IoT is the first AI company bringing strong analytics to the railway. We use next-generation technology to deliver data for better decision making.
The Global Warming Challenge
Global warming poses significant challenges for railways, primarily due to its impact on infrastructure and operations.
SYNAP IoT are first movers on using AI to help predict Critical Temperatures in continuous welded rails using RailGuard.
OUR SOLUTION
RailGuard
SYNAP IoT RailGuard is an AI driven predictive maintenance system which helps infrastructure managers monitor rail temperature in real-time. Their employees will be able to make data driven decisions regarding slow orders, possible rail buckles and cut costs on maintenance
Enhancing Railway Operations with AI-Based Condition Monitoring
At SYNAP IoT, we are dedicated to leveraging cutting-edge technologies to improve the safety, reliability, and efficiency of railway operations. One such technology that we employ is AI-based condition monitoring, which offers a wide range of benefits for railways.
Predictive Maintenance: Our AI algorithms analyze vast amounts of data collected from sensors installed on tracks. By detecting anomalies and predicting potential failures before they occur, we can help schedule maintenance proactively, minimizing downtime and reducing maintenance costs.
Optimized Asset Management: With AI-enabled condition monitoring, we gain insights into the health and performance of tracks and switches. This allows us to prioritize maintenance activities, allocate resources efficiently, and extend the lifespan of assets.
Enhanced Safety: Continuous monitoring of critical infrastructure enables us to identify safety hazards and risks in real-time. By taking proactive measures to prevent accidents, we ensure the safety of passengers and crew members.
Improved Reliability and Efficiency: By reducing unexpected failures, minimizing delays, and optimizing maintenance schedules, AI-based condition monitoring enhances the reliability and efficiency of railway operations. This leads to improved service reliability and increased customer satisfaction.
Data-Driven Decision Making: Our AI algorithms analyze data from various sources to provide actionable insights for decision-making. Whether it's determining maintenance priorities or optimizing operational strategies, data-driven decisions lead to better outcomes for our railway systems.
Cost Savings: Implementing AI-based condition monitoring results in significant cost savings for railways. By reducing maintenance costs, extending asset lifespan, and avoiding costly downtime, we ensure cost-effective operations and improved financial performance.
At SYNAP IoT, we are committed to embracing innovation and leveraging technology to address the challenges facing modern railways. With AI-based condition monitoring, we are transforming railway operations, enhancing safety, reliability, and efficiency for the benefit of our passengers and stakeholders.
Contact us today to learn more about how AI-based condition monitoring can revolutionize your railway operations!
Improved Safety
Minimize delays
Improved Maintenance
This is our mission at SYNAP IoT:
Remote monitoring of rails will keep people of the track and in harms way.
Temperature monitoring and prediction using AI will help prevent derailments and improve operation scheduling because precise slow orders can be enforced only where needed.
Cost of maintenance will go down when using AI to digitally show where track problems occur.
Slow order prediction
With our data analytics and AI models we help predict what the maximum rail temperature will reach during the day.
Slow orders are enforced based on the weather forecast and because the temperature is not the same over long distances we help predict what the actual rail temperature will be based on local data like current weather, current rail temperature, forecasted weather condition and physical conditions.
With our machine learning algorithms we are able to help rail operators make decisions based on data and no longer a weather forecast.
These predictions is helping rail operators save millions as slow orders will be shorter and only in parts of a line and not the entire line.
RNT/SFT monitoring
Ensures safe and reliable rail operations
· Monitor thermal expansion enabling action where needed
· Less delays as speed reductions can be based on data
Cant/Tilt
Early detection of abnormalities
· Tamper validation and execution effectiveness
· Optimize the balance between speed, stability and comfort
· Data driven decisions on maintenance requirements
Curve Angle monitoring
Important for maintaining safety, optimizing track maintenance
· Regulatory compliance
· Energy efficiency
· Safety
· Track maintenance
· Improving ride quality