with Azure IoT Hub Cloud Platform

BUILD YOUR IOT CLOUD SOLUTIONS WITH OUR
IN-DEPTH EXPERTISE IN AZURE IOT HUB

IoT cloud platforms are cloud-based middleware software and considered as the ‘plumbing’ of IoT solutions. They deliver IoT and cloud computing capabilities as a service over an end-to-end platform. IoT cloud platforms provide ready-to-use software components which can be customized to suit your IoT cloud solution with minimal effort.

AZURE IOT HUB CLOUD PLATFORM

Microsoft describes Azure® IoT Hub as “a managed service, hosted in the cloud, that acts as a central message hub for bi-directional communication between your IoT application and the devices it manages”. They claim that Azure IoT Hub can be used to build IoT solutions and connect virtually any device with reliable and secure communications between millions of IoT devices and a cloud-hosted solution backend.

Azure IoT Hub provides several cloud services and SDKs to build end-to-end IoT solutions catering to various real-life situations. These services and SDKs empower you to enable IoT for devices, capture device telemetry data on cloud, run near real-time analytics, trigger alerts, and integrate with external applications, store data and run real time anomaly detection or predictions based on machine learning models. Azure IoT Hub cloud platform is metered on the number of operations between the cloud and devices or applications.

AZURE IOT HUB EXPERTISE

Thinxtream has extensive expertise in developing IoT cloud solutions for your Connected Products and Smart Services using the Azure IoT Hub cloud platform.

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

We have built strong expertise in following core services from Azure IoT Hub.

• 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
• Provide geographic context to your location-aware IoT applications with geospatial functionalities using Azure Maps
• Field Gateway support for IoTification of low power devices, and devices without internet connectivity
• Build solutions using industry-specific application templates from Azure IoT Central
• 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