This article will introduce how to build an industrial IoT platform that integrates the capabilities of industrial data collection, aggregation, cleaning, storage and analysis, and visualization and display based on open source and commercial software in the community. Based on this solution, readers can adjust this solution design according to their own needs for building the industrial internet platform that meets actual business needs and accelerate the realization of industrial intelligence transformation.
With multiple protocols co-existing in the industrial domain, there is no avoiding the problem of how to connect heterogeneous devices and converge data for subsequent edge or cloud computing. Two general solutions are currently available:
To integrate the different needs of OT and IT at the edge, EMQ officially launched a solution for industrial internet cloud edge collaboration to help enterprises in the field to cope with the problems and challenges faced by the edge of industrial Internet. This solution is suitable for deployment at the edge, with various industrial protocol parsing, multi-source data access and data analysis capabilities, and can quickly implement the functions of the edge layer under the industrial Internet architecture in a cloud-edge collaboration way.
This solution can implement the industrial protocol parsing, data aggregation and streaming analysing at the edge and store the data that is through streaming analysing in a lightweight time-series database deployed at the edge. The applications running at the edge-end can get data from the time-series database and process it and present it to the user. The Edge Manager running at the edge-end provides a management console for easy software configuration and management.
Higher requirements for real-time, can run as an autonomous independent application on the edge of the gateway or IPC, no interaction with the cloud. All computation and storage in this solution are implemented at the edge, so there are certain requirements for the hardware. Users can deploy the software and applications separately on multiple hardware devices according to the actual situation.
This solution will use these software products in the following list.
No. | Name | Provider | Open source |
---|---|---|---|
1 | EMQ X Neuron | EMQ | No - 1 |
2 | EMQ X Edge | EMQ | Yes, Apache 2.0 |
3 | EMQ X Kuiper | EMQ | Yes, Apache 2.0 |
4 | Edge manager | EMQ | No - 2 |
5 | TDengine | Taosdata | Yes, GNU AGPL v3.0 |
6 | Grafana | Grafana Labs | Yes, Apache 2.0 |
1:
In the future, Neuron plans to open-source its basic functions. Currently, users can download the trial version and use it for free. If there are not enough data collection points for the built-in trial version, you can apply online through EMQ website.
2:
Users can use all features in the free version for free, except for a limited number of managed nodes. If you want to try more node management features, you can apply online through the EMQ website.
The description of basic functions of product
Supported hardware and software environments
No. | Name | x86*32 | x86*64 | ARM 7 | ARM 64 | PPC64 | Mac | Docker |
---|---|---|---|---|---|---|---|---|
1 | EMQ X Neuron | ☑ | ☑ | ☑ | ☑ | ☑ | ||
2 | EMQ X Edge | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ |
3 | EMQ X Kuiper | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ |
4 | Edge manager | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ | ☑ |
5 | TDengine | ☑ | ☑ | ☑ | ☑ |
To make it easier for users to try, the demo scenario utilizes Docker and Docker compose technology for quick deployment, and users can follow tutorial to experience the solution on a virtual host, IPC, or computing-powered gateway. In the actual business system deployment process, users can deploy directly with binary installation packages in the production environment as needed, which will run more efficiently.
In this sample scenario, the data is sent out via the Modbus TCP protocol to simulate temperature and humidity data, which enters the system to achieve data collection, aggregation, cleaning, storage analysis and visualization capabilities. The following is a visualization report of temperature and humidity presented in Grafana.
Note: The container images released by TDengine are by default for x86*64 environments, so if you want to switch to an ARM architecture, you need to manually change docker-compose.yml
to point to the correct version.
This approach differs from the above in that it introduces the concept of cloud edge collaboration, with underlying distribution and orchestration capabilities for container-based applications on the edge similar to those provided by KubeEdge/IEF. The centralized management of instances such as Neuron, Edge and Kuiper enables online management and updating of data collection, aggregation and analysis logic at the edge in the cloud. Also in the cloud, by deploying EMQ X Enterprise's distributed, highly available clustering capabilities to access and analyze data from devices distributed across different edge endpoints.
This solution is used in business scenarios where there are multiple management nodes that need to be controlled and managed in the cloud in a centralized and unified way for edge nodes located in different locations. With this solution, users do not need to go to the location of the physical edge nodes to manage them, which greatly improves management efficiency.
This solution will use the following products except the products which used in the solution 1 edge-end.
No. | Name | Provider | Open source |
---|---|---|---|
1 | EMQ X Enterprise | EMQ | No - 1 |
2 | IEF | Huawei | No - 2 |
1
: EMQ X Enterprise Enterprise IoT MQTT messaging platform supports one-stop access for millions of IoT devices, MQTT & CoAP multi-protocol processing, and low-latency real-time message communication. Supports built-in SQL-based rule engine, flexible processing/forwarding of messages to back-end services, storage of message data to various databases, or bridging to Kafka, RabbitMQ and other enterprise middleware.
2
: IEF intelligent edge platforem (Intelligent EdgeFabric) is the commercialized version of KubeEdge, Huawei's open-source cloud edge collaboration platform, which meets customers' demands for remote control of edge computing resources, data processing, analysis and decision-making, and intelligence, and provides users with a complete integrated service of edge and cloud collaboration.
Based on the industrial internet infrastructure capability platform built by this solution, users can implement efficient and low-cost industrial Internet device connectivity, acquisition and analysis. Whether it is a lightweight pure edge solution or a cloud-edge collaboration solution with a more complex deployment environment, it can be realized by this solution.