Thinxtream Azure IoT Hub
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Thinxtream can rapidly enable
your Connected Products and Smart Services business


Thinxtream has had a long partnership with Microsoft®, and has extensive knowledge in building IoT solutions using Azure® IoT Hub, Azure IoT Edge, and other Azure services. With our deep understanding of the Azure IoT backbone and leveraging Azure IoT Suite, Thinxtream is able to architect and quickly deliver value-added IoT solutions to customers to fulfill their dynamic business and market requirements.

  • Communications using Messaging, File transfers and Request-Reply methods
  • Declarative Message Routing for sending device-to-cloud messages to other Microsoft services like Azure Stream Analytics, Azure Functions, Azure Service Bus or Azure Storage account
  • Integration with Azure Service Bus and Azure Logic Apps for Enterprise Integration and Analytics using tools like Microsoft Power BI®
  • Device Twins for a query-able store for device metadata and synchronized state information using JSON
  • Secure communications using X.509 certificates and access control at a per-device level
  • Monitoring for device connectivity using Operations Log and Activity Log
  • Device identity management using Azure IoT Hub Identity Registry
  • Support for AMQP, MQTT, HTTPS, or custom protocols for proprietary devices
  • Automatic, Zero-touch, Just-in-time provisioning of millions of devices using IoT Hub Device Provisioning Service
  • Field Gateway support for IoTification of low power devices, and devices without internet connectivity
  • Develop IoT solutions in C#, Java, Node.js, .NET Core, etc. and for various platforms (Linux®, RTOS, Windows®)
  • Use Azure IoT Edge, a Microsoft IoT service, to analyze device data and run business logic on the devices
    • Perform time sensitive decisions on device to reduce latency
    • Provide device management services, protocol translations, and enforce security
    • Deploy and run trained models from Azure Machine Learning Studio as Docker Containers on the Azure IoT Edge devices
    • Run Azure Functions and Azure Stream Analytics for real-time processing of incoming data on the field gateway or on the IoT Edge device
    • Develop business logic in Java®, .Net Core 2.0, Node.js, C and Python™
    • Build, test and deploy Deep Learning and AI solutions with VS Code extension
    • Integrate Apache Spark™ Machine Learning Pipelines with Microsoft Cognitive Toolkit and OpenCV library
    • Deploy Azure Machine Learning model as Web service
    • Pre-trained models based on Residual Deep Convolutional Networks for Transfer Learning



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