A Guide to Harness the Power of IoT through Azure
Azure enables a developer to expedite application development on the account of pre-built templates. Due to this, building and managing enterprise, mobile, web, and Internet of Things applications is no longer an uphill battle. Azure’s support for large spectrum of operating systems, programming languages, frameworks, and tools makes it the most preferred choice amongst developer community.
Being in tandem with the latest technological trends, Microsoft Azure is making strides to harness its global infrastructure of servers and cloud services and leverage the power of Internet of Things (IoT). Microsoft’s endeavor is in sync with the business conditions of this age as more companies are joining the flock that relies on hard data generated from a network of connected machines.
With exponential growth in number of connected devices, machine-to-machine communication offers a set of advantages and challenges. The advantages are numerous such as monitoring assets in real time to improve operational efficiency, deriving predictive maintenance insights, and employing advance data analytics to explore new business models. Though a typical IoT solution acts as a gateway to actionable insights; implementation of the solution is full of intricacies in collection, analysis and storage of data, data visualization, and system integration. Sometimes, the organization build IoT solutions in-house to mine the data from field devices, but face problems while scaling up the operations due to inadequate infrastructure support and storage capabilities. Supporting applications that run in different operating environments is another hurdle and deep know-how about machine-to-machine communication becomes a necessity to ensure successful implementation of IoT suite.
Azuer IoT helps the users to mitigate the complexities in deploying smart devices and deal with related issues. In its pursuit to empower the users with quickly deployable IoT solution, Microsoft offers pre-configured solutions, which are end-to-end implementations built to generate telemetry. Using IoT software development kits (SDKs), which are available on code repository like GitHub, the user can meet project requirements with customization and extension of these solutions. The pre-configured solutions use following services:
Azure IoT Hub Service
This service is at the center of Azure IoT platform. The service acts as a gateway in the device-to-cloud and cloud-to-device communication and other key IoT suite services. Azure IoT Hub provides support for the AMQP 1.0 with optional WebSocket support, MQTT 3.1.17, and native HTTP 1.1 over TLS protocols.
Azure Stream Analytics
The user is empowered with real time data analysis on account of this service. The service endues the user with power to process incoming data, aggregate it and decipher the events. Messages containing metadata or command responses can also be processed, which can be delivered to other devices.
Azure Storage and Azure DocumentDB:
Data storage capabilities rely on these services. DocumentDB is used to store device metadata whereas blob storage is used to store data transmitted by the devices.
Azure Web Apps and Microsoft Power BI:
These services provide the data visualization capabilities. Power BI endues the user with build interactive dashboards that use IoT Suite data.
To understand the capabilities of pre-configured solutions, it will be prudent to have brief overview of architecture. The architecture encapsulates following three crucial areas of an IoT solution and they are:
The cloud native gateway provides endpoints for device connectivity and ensures two way communication between the cloud and the devices. There is an array of components in the back end, which is accountable for device registry and discovery, data collection, transformation, and analytics.
Data processing, analytics, and management
The cloud gateway facilitates the entry of data from field devices, but further flow of data is ensured by data pumps and analytics tasks. Data pumps do not modify the data while moving or routing it, whereas analytics tasks process the events. The same set of data can be used by different stream processors for variety of purposes. At this stage, multiple tasks are performed and they are data storage, device registry and provisioning, analytics and machine learning.
Presentation and business connectivity
The business integration and presentation layer is accountable for amalgamating IoT environment with the business processes of an enterprise. The user can view and analyze the data collected from the devices due to this layer. Dashboards present the data in the readable format.
Business systems need to leverage Azure, but how?
The business integration layer integrates IoT environment with numerous business systems like CRM, ERP and other applications. The IoT solution uses business connectors or EAI/B2B gateway capabilities.
Now, let us know about the benefits of deploying Azure IoT suite:
The connected devices generate large amount of data and eventually the user gains insights after processing the data streams. Again, the user can track nuances related to real time data streams.
This plays crucial role in raising a maintenance ticket for the assets that are being monitored. The feature merits an enterprise with improved operational efficiency. In one of the instances, ThyssenKrupp in association with CGI, developed an IoT solution that leveraged Azure IoT service to track sensors and systems in its elevators. ThyssenKrupp was able to capture key parameters like motor temperature, shaft alignment, cab speed etc. The data capture eventually helped its technicians with instant diagnostic capabilities and data visualization.
The companies are allowed to integrate Azure services with their back end systems, so the data exchange between Azure and their existing systems can take place easily.