The Infosys Logistics practice leverages Industrial Internet of Things (IIoT) to develop smart railroad networks. We integrate real-time data from IoT sensors embedded in components such as brakes, wheels, engines, wagons, and rail tracks, with train control systems, freight information systems, and driver performance reports to boost the performance of enterprise and station-level functions.
An IIoT-enabled rail network rationalizes costs through predictive maintenance of assets, safe operations and energy efficiency. Our algorithms predict diverse variables, ranging from stress on rail tracks to wagon / tanker lifespan, to avoid interruptions caused by equipment breakdown, adverse weather conditions or non-availability of personnel. Further, predictive maintenance minimizes planned downtime while extending the life of rail infrastructure.
Our cloud platforms support the ingestion, processing and storage of data from IoT applications, enterprise systems and machine-to-machine communication devices for advanced analytics. Our analytical models and artificial intelligence-based systems consume enriched data for auto-correction of shipment schedules. Data visualization enables dynamic pricing of freight orders. Significantly, it aligns sales plans and network operations to ensure timely and damage-free shipment, even in extreme weather conditions.
Analytical tools help logistics providers aggregate global demand, while predictive maintenance of heavy equipment rationalizes warehousing and distribution costs.
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Case Study
Case Study
Case Study