How do IoT platforms fit in?
IoT platform: a key element that acts as a bridge between IoT devices and the digital ecosystem.
Introduction
There is an important element within the IoT ecosystem, gaining more attention since it can interact as a bridge between IoT devices and the digital world: the IoT platform. In the following image, we have a reference diagram representing this idea.
The IoT devices establish secure connections with the IoT platform, and the platform enables the exchange of IoT-based data with the digital ecosystem. One of IoT platforms’ main features is device lifecycle management (OTA, provisioning, devices and security management, etc.). Beyond this, the platform’s goal is to integrate device data with other digital solutions such as data visualization tools, data storage strategies, web/mobile application integration, augmented/virtual reality, and data analytics.
How do IoT platforms fit in?
The diagram below represents a model of what companies are looking for in the context of digital transformation and Industry 4.0.
At the left, across the entire model is the business value chain: oil and gas, mining, automotive, insurance, retail, banking, etc.
At the bottom, every customer has an infrastructure with three main components: storage, computing, and communications. This infrastructure enables two data sources, the well-known data from software tools (business applications) and data from assets (Things), which maybe is a new element for you.
- The first element in green is the IoT platform. The main idea of this component is to model the digital representation of assets and enable, as seen before, the interaction of IoT data with digital solutions, especially other software tools (ERP, CRM, CMMS, etc.) or enable the development and integration of applications based on IoT data and other data sources to provide more context to end-users.
- The second element in green represents the assets (Things). Nowadays, we have more sensors and devices interacting across business value chains. These assets are expanding from a silo scenario to integrate different processes in many cases. For example, a company has its manufacturing control systems connected to the internet and its vehicle’s fleet used for product delivery.
From these two data sources (software tools and IoT data), the next component of the model is applications, dashboards, and reports. Developed not only in a conventional way (mobile/web apps) but based on new trends, we can have augmented/virtual reality and analytics-based applications.
At the top of the diagram, we have an element that represents the collaboration between all the elements of the model and users to enable data-driven decisions to improve their forecasts, return of investment, user experience, efficiency, safety, security and enable predictive maintenance, a new desired feature for many industries.
Finally, at the model’s right, there is an arrow across the model that represents two crucial components: security and sysadmin for the orchestration of all the components within the model.
Digital twins and IoT platforms
One of the IoT platforms’ purposes is to model the digital representations of assets. In the context of Industry 4.0 and Industrial IoT (IIoT), there is a huge potential for this type of implementation that can be named as digital twins-based implementations. As shown in the following image, the idea is to create the digital representation considering several data sources of each asset that is part of the processes.
In the following image, we have a similar diagram that the one used as the introduction, but this time focused on the context of IIoT. Once the digital representation of the assets is implemented, the IoT platform enables the interaction between the physical and digital world. The asset IoT data ingestion comes from the control systems through the convergence of operational technology (OT) and information technology (IT). This IoT data is complemented within the asset model with data from other sources such as databases and/or business applications (ERP, CRM, CMMS, etc.). Once all this information is integrated, it enables the collaboration of end-users by interacting with the digital twin with applications based on data visualization, data analytics, and augmented/virtual reality.
IoT platforms main components
Before getting into reference architectures, let’s understand the main components of an IoT platform.
- Devices support: vendors provide SDKs and, in some cases, Real-Time Operating Systems (RTOS). Here the main aspect is integrating communication and connectivity capabilities within the Firmware/Embedded software of the devices to enable the secure connection with a given IoT platform. It is important to notice that in some cases, the SDKs can be used as a mechanism to connect software-based services instead of devices with platforms.
- Connectivity: vendors provide different internet-based connectivity methods between devices and platforms; one common example is enabling an MQTT broker or similar strategies oriented to open IoT protocols. In other scenarios, vendors can have their proprietary protocols.
- IoT services: this is the core of an IoT platform in which, as mentioned before, the idea is to enable all the device management features and to develop the assets modeling, adding business logic services, and creating integration with other types of services and applications.
- Built-in connectors: this an essential feature depending on the scenario in which you want to integrate an IoT platform, built-in connectors that you will have available to integrate for a specific use case. For example, an SAP connector to integrate from the SAP maintenance module data to the IoT platform application that you need to develop.
- Security: this main component might be implicit in other components, but it is important to remark, due to the need of having mechanisms to manage the secure connection between the devices and the platform, not only for data exchange but to allow the devices management reliably.
IoT platforms reference architectures
Considering that in this article, we have been focusing on IIoT and based on the most recent Gartner Magic Quadrant for Industrial IoT Platforms, let’s now take a quick review of the reference architecture from two of the leaders of this magic quadrant: PTC and Azure.
PTC — Thingworx
The ThingWorx platform from PTC is a complete, end-to-end technology platform designed for the industrial Internet of Things (IIoT). It delivers tools and technologies that empower businesses to develop and deploy applications rapidly and augmented reality (AR) experiences. In the following diagram, we have the platform architecture in which we can find four main elements:
- IoT data sources: in this case, mainly grouped in three components, the devices using the Thingworx Edge Microservice or the Edge SDKs to establish a secure connection with the IIoT Platform AlwaysOn proprietary protocol. The second group is the devices from the OT ecosystem that are mainly connected with the platform through the Thingworx Industrial Connectivity that support a wide variety of industrial protocols. And finally, other complementary data sources that, through SDKs, can establish a connection with the platform.
- Thingworx foundation: this is the IoT core of Thinworx and is also divided into three components, the Thingworx Composer, in which the development team implements all the assets modeling, business logic, and analytics definition through services. The second element is the persistent provider and what this means is that the platform needs a database to manage the IoT data strategy for persistence. As seen in the diagram, many alternatives are supported. Finally, the third component is the Thingworx Mashup Builder that enables web-based applications integrating the models, the business logic, and the data strategy consuming data persisted within a given database.
- Interactions: Around Thingworx foundation, we can see different types of interactions first the end-users that are going to consume through the REST API the application from web/mobile endpoints, and then we have several features that are enabled through dedicated modules or connectors to facilitate the integration of other types of applications related to augmented/virtual reality, data analytics, business system integration, databases integration and so on.
- Security: Across the entire architecture diagram, we have a Secure Data Flow that aims to represent all the strategies oriented to manage the secure connection between the IoT data sources, the platform, and the end-users’ applications.
Microsoft — Azure IoT
Azure IoT is a collection of managed and platform services across edge and cloud that connect, monitor, and control billions of IoT assets. It also includes security and operating systems for devices and equipment and data and analytics that help businesses build, deploy, and manage IoT applications. In the diagram below, we have the reference architecture in which we can also find four main elements:
- IoT data sources (Things): We have two types of devices in this architecture. In the first case, we have devices running an SDK or the Azure RTOS to manage the connection with the platform’s entry point. In the second case, we have edge devices that perform data processing on the device itself or in a field gateway based on Azure IoT Edge. It is important to keep in mind the concept introduced by Azure that a high level, there are two ways to process telemetry data, hot path and cold path. The difference has to do with requirements for latency and data access. The hot path analyzes data in near-real-time as it arrives. The cold path performs batch processing at longer intervals (hourly or daily).
- Insights: here, there is a component that can also be seen from the devices (Things) point of view, in terms that provide the entry point to the platform and is supported through SDKs within the devices. This element is the Azure IoT Hub with the DPS (device provisioning service) that enables secure communication between your application and the devices. From this point, the idea is to facilitate the integration of other Azure services and IoT data, which is analyzed and turned into actionable knowledge either by people or artificial intelligence (AI).
- Actions: This component is related to the way people respond to those insights (second element of the architecture) and connect them to their business, as well as the systems and tools they use through other Azure-based services.
- Security: Similar to the previous reference architecture, in this case, Azure provides the Azure IoT security service to, among other things, guarantee secure connections and protect cloud services.
Conclusion
In this article, we reviewed how IoT platforms can be seen as a bridge between IoT devices and the digital ecosystem. Then the introduction of a model in the context of IIoT and Industry 4.0 to identify how these IoT platforms fit in the context of solutions-oriented to facilitate data-driven decision making. We saw the appearance of the digital twin concept developed from the point of view of an IIoT solution. This enables explaining the main components of an IoT platform. Finally, at a high level, we reviewed the reference architecture from two of the leaders of the most recent Gartner Magic Quadrant for Industrial IoT Platforms: PTC and Azure.
Suggested readings
If you are interested in knowing more about implementing a solution based on an IoT platform, I invite you to read the article A digital twins PoC.
If you are interested in learning more about PTC — Thingworx, visit the Thingworx developer portal.
And finally, if you are interested in learning more about Microsoft Azure IoT, visit Introduction to Azure IoT.
