Service

IoT & Edge Computing

Real-time analytics at the edge: sensor integration, protocol translation, predictive analytics on resource-constrained devices.

Modern field deployments increasingly do their analytics at the edge, closer to where the data is generated, with limited dependence on back-haul connectivity. We design and build edge-computing applications for rail-spec and industrial platforms. Our work includes protocol translation between legacy and modern systems, predictive analytics that run on resource-constrained devices, and the operational discipline to keep these systems running in the field for years.

Capabilities

— Edge-deployed predictive analytics (battery-life prediction, switch-machine health, power-quality monitoring)
— Protocol bridging (legacy to modern)
— Sensor integration and data fusion
— Local-first architectures that ride out network failures

Technologies & Protocols

Sparkplug B MQTT SNMP Genisys ATCS Datagram REST CoAP Edge ML inference

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Related case studies

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Complete edge software stack for CSX grade crossing monitoring that unified multi-vendor field equipment and built the first native CAMS/WAMS integration outside of Siemens.

ATCS Genisys CAMS/WAMS OCG +7 more

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Related products

Wayside Watcher™ → BattTrackIQ → DataBridgeIQ → E.D.D.S. → PowerGuardIQ → RailQueryIQ → SwitchGuardIQ →

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