IIoT platforms drive change

Strange New Creatures: Industrial IoT Platforms as Drivers of Change

Hervé Coureil, Chief Digital Officer at Schneider Electric, says: “It’s not so much about the platform. It’s about how you impact the world with digital technology.” A platform is an enabling entity that thrives on the innovative power and collaborative zest of those working on it. A platform built for its own sake is something of an impossible object: rather than existing in isolation, platforms live because of the processes they facilitate. 

This feeds into the even bigger question of how digital technologies enhance lives. Because, at the end of the day, it may not even be about the tech. A recent publication puts it succinctly: Digital transformation is not about technology. It is about changing mindsets and generating possibilities. It is about the users, and the sense that needs are being met. 

The very concept of an IIoT platform

The very concept of a platform for the Industrial Internet of Things (IIoT) lives up to this challenge. Ideally, IIoT platforms are highly scalable, flexible, and interoperable. This is the hardware-and-software bundle that connects thousands of devices and allows for the remote management of multiple applications and massive flows of data.

IIoT platforms are built with the specific aim of being maximally user-centric and geared towards comfort. While they may not be your typical point-and-click, plug-and-play solution (as they still require a certain level of developer know-how), IIoT platforms are known for their usability. 

An industrial IoT platform covers the fundamental prerequisites of data-driven manufacturing while allowing you to build and scale up. You are given both the operating environment and the building blocks for application development. 

IIoT platforms hold the promise of cost reduction, improved operations, the generation of new business models, and novel capabilities to transform data into value. These can be industry-specific, geared towards particular use cases (such as inventory management, worker safety, monitoring of manufacturing processes, etc.), or particular outcomes such as optimizing overall operational efficiency. 

Also, IIoT platforms allow for faster, less cost-intensive harvesting of higher volumes of complex machine data from networked IoT endpoints. Integrating siloed data, enhanced condition monitoring, as well as better insight through integrated data analysis and data visualization solutions, have been pointed out as key differentiators that will cause IIoT platforms to eventually outpace legacy control systems. 

According to Gartner’s Magic Quadrant for Industrial IoT Platforms,

by 2023, 30% of industrial companies will have full, on-premise deployment of IIoT platforms, an increase from 15% in 2019.

The IIoT platform wishlist

Industry analysis has uncovered that an IIoT platform is expected to have the following:

  • Device management functionality. This is how you connect to a multitude of IoT devices, sensors, machines, and industrial equipment, create device groups, and are better equipped to both identify and recover from device failure. 
  • Data management functionality.  This is how you monitor IoT data collection, data storage, and the continuity of your data flow. You want to be able to perform analytics on the data streamed from devices to extract actionable insights from it. 
  • Integrability. You need development tools, software development kits, and APIs.
  • Software that enables security audits and ensures compliance, but also ways to prevent data loss and to detect breaches.
  • Flexibility.  You want to have no-code interfaces to allow a range of users to access job-specific applications.
  • Hybridity. A combination of cloud computing, on-premises deployment, and edge computing.

The IoT edge 

Using compute and analytics at the edge is beginning to slowly overshadow cloud computing. Depending on needs, immediate and fast insight may be a more pressing need than in-depth yet time-intensive cloud computing. 

Edge platforms are geared towards the machines they connect. They have become “sophisticated intelligent gateways” that interact with local apps and cloud data aggregators. Edge platforms can talk to a variety of machines and protocols. They can also integrate tools that perform advanced analytics at the edge to generate insight fast. At the same time, edge platforms are interoperable with cloud services, and are flexible enough to integrate tools from other vendors.

How to bring IoT to the edge fast?

The combined forces of our IoT device management studio and our data science studio forge a complex end-to-end solution applicable to a wide spectrum of IoT scenarios. With the Record Evolution platform, you have a fully-fledged IoT suite for the remote management of devices and device groups as well as an application enablement platform. On top of that, you have the full cloud data warehouse infrastructure to receive the data streams harvested from each IoT device. This is how you build your insight-enabling analytical data environment.

Closing the circle of IoT development and deployment

As shown below, once you have trained your machine learning model in the cloud, you can use the platform’s over-the-air development environment to package it as an IoT application. The app is now ready to be deployed. You now roll out to a variety of connected devices. This is how you bring back the logic and models to the IoT edge.

Figure 1. How the IIoT platform brings AI to the IoT edge

In this way, a full circle is formed. We start from data acquisition from sensors and smart devices, collecting, pre-processing, and aggregating the data at the gateway.

The next step is transmitting the data to the cloud data science studio. There, you perform more advanced analytics on your data or train machine learning models.

Finally, the insights gained from your analytics in the cloud can be packaged as IoT apps. These can be rolled out back to the edge devices.

A full circle is formed by using just one single platform: from data acquisition, data transformation, and analytics all the way to deployment at the IoT edge. 

IIoT platform application areas

The platform can be used in a wide variety of smart manufacturing applications in the manufacturing industry and beyond. Beginning with asset tracking and condition monitoring on the shop floor to industrial automation, all the way to overseeing the entire manufacturing process from a platform that serves as your single source of truth. You can read more about this in the article “Utilizing IoT and the Artificial Intelligence of Things in Manufacturing“.

For an in-depth discussion, get in touch with one of our experts to get all the details.

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About Record Evolution

We are a Data Science & IoT team based in Frankfurt am Main, committed to helping companies of all sizes to innovate at scale. So we’ve built an easy-to-use development platform enabling everyone to benefit from the powers of IoT and AI.