The IoT is widely used in the private sector at home and has many use cases, including remote camera and security sensors access, lighting control, air quality monitoring, voice assistance, smart locks, and more.
IoT brings even more benefits to businesses, so IIoT (Industrial IoT) platforms continue to evolve to help enterprises increase their potential.
You can see a distribution of vendors providing IIoT Platforms in Image 3.
According to the Gartner Magic Quadrant, Microsoft, PTC, Hitachi, and Software AG are the most noticeable. AWS and Siemens are also worth mentioning.
But what is the IIoT Platform?
It’s a set of services (and sometimes hardware) that:
automates IIoT data aggregation,
pushes it to a central cloud, edge location, or private data center,
and provides tools for integration with other services like AWS S3, Redshift, or OpenSearch.
The goal of an IIoT Platform is to:
reduce costs compared to legacy operational technologies (OT),
and gain the benefits of cloud technologies, such as availability, scaling, DR, etc.
These platforms are extremely useful for a wide range of manufacturing, transportation, and energy enterprises, including car manufacturers and automotive businesses, food and beverage industries, metal and industrial manufacturers, chemical organizations, electric and gas facilities, transport subsectors, and many others.
More specifically, IIoT platforms provide:
Advanced device management. Services that simplify a device configuration, pairing, and cloud IoT setup.
Better cloud integration. Integration with other cloud services is simpler; for example, AWS Greengrass allows access to other AWS services through an AWS API or Lambda function via a secured communication channel.
IoT fleet analytics. A service that allows analyzing the state of your IoT fleet. It may give the health status of each device, a list of metrics, and integrate with other services for visualizing the data.
Firmware updates automation. A simplified process for maintaining continuous deployment of the firmware updates to a fleet of your devices.
High security. A secured communication channel between devices and a cloud. Fine-grained permission and access separation. Encryption keys rotation and automatic security audits.
In this paper, we cover a few such platforms that can be used for IIoT. We also provide a brief overview of related cloud services that can be used with IIoT; for example, services that allow device connection via private 5G networks by creating a distributed cloud and utilizing edge computing principles.
We must also remember that industrial companies use specific protocols to communicate with sensors; for example, DLMS/RS232 or IEC104/101 in conjunction with SCADA systems.
In these cases, it's still advised to connect these devices to a distributed IoT cloud. By applying a cloud connection to a proprietary system such as that shown in image 4, we benefit in several ways including cloud monitoring, OTA updates, data streaming, and backup.
For example, we may use AWS IoT core to access remote IoT devices through MQTT/HTTP and a hybrid IEC104 edge adapter to make communication with a cloud through managed Kafka service.
Data from services may be processed in the cloud using serverless lambda functions and S3/Athena data sources for visualizing data in managed Grafana (image 5).
Or, we may pick another strategy and start using stateful services as shown in image 6.
In such an architecture, we put all the processing logic into the K8S cluster, which can then be easily ported into the different cloud providers or even spread across multiple providers in parallel.
We can also extract all sensitive data and store it in on-premises data centers to comply GDPR/HIPAA policies.
Still, there is one component lacking here: edge computing. It's essential to save cloud throughput and gain additional system performance and data protection. This can be achieved by AWS Greengrass or Azure IoT hub, which we’ll explore in an upcoming section.