Product advice: How cloud and edge coordinate, thrive in the IIoT era
With efficient cloud and edge coordination, edge devices provide a better understanding of what’s going on in the field, work efficiently and deliver a better user experience, according to a company with a Control Engineering Engineers’ Choice Award product. See four steps toward a cloud and edge Industrial Internet of Things (IIoT) ecosystem.
- Understand the four steps toward a cloud + edge IIoT ecosystem.
- Examine how a cloud and edge design delivers better user experiences.
Contemporary industry features a growing number of devices distributed on various industrial sites. Given long-time operation, it is inevitable some of them may go wrong now and then. To identify problems earlier and take preventive measures, it is necessary to keep track of their working status. Maintenance engineers are traditionally sent on-site. However, this can incur considerable costs and, more often than not, problems cannot be promptly identified.
The development of Industrial Internet of Things (IIoT) has enabled those onsite devices to be connected to the Internet, so their operation status is constantly monitored from a central location. Whatever happens can be seen from the cloud in real time and once a fault occurs, engineers can locate the problem before the screen and take immediate action.
Four steps toward a cloud + edge IIoT ecosystem
As more devices are connected to the Internet and generating increasing data volumes, manufacturers and users are seeking more efficient maintenance and insights from data to facilitate growth. This implies deeper digging of data, better processing and analytics. All those demands are creating greater technical challenges for a coordinated “cloud and edge” IIoT ecosystem.
1. Collect data from different devices
Devices deployed on industrial sites keep capturing data from different parts of the site, monitoring both the machines and the environment. As those devices are built with different interfaces (serial ports, Ethernet ports, Bluetooth, Wi-Fi), it is not easy to acquire data from them all. Various types of devices on site are generating massive amounts of data, which is a great challenge for the gateways expected to collect and process them.
Different devices communicate with different protocols. Even within the same category, there can be quite a few options. Take programmable logic controllers (PLCs) as an example. There are several major players in the industry and each has its own protocol. Meanwhile, some manufacturers communicate via their private protocols. This creates compatibility problems for users, as most traditional gateways that transmit data support only a few of those protocols. This means several kinds of gateways are needed for one site, which implies huge expenditure on equipment and high costs for brand switch.
As onsite devices become more diverse and the above-mentioned problem gets acute, it is necessary that multiple industrial protocols be integrated and private protocols be compatible too, so data from different sources can be transmitted by an all-in-one IIoT gateway.
2. Pre-process data on the edge
In the era of cloud computing, data are uploaded to the cloud for processing, storage and analysis. As massive data being generated, they are creating a heavier load to the cloud. Think about if all data should be sent to the cloud bit by bit, wait for the cloud to receive them all and reply with command (or sometimes no command at all) before further action is taken. This means great latency in data transmission. Even though 5G can solve the speed problem, the cloud is overloaded with huge amounts of data.
This is where edge computing comes in. With pre-configured conditions or programmed tools, data collected from different devices can be filtered near where they are generated (the “edge”). Some of them can be processed locally. For example, if certain threshold is reached, the gateway can immediately respond by, say, sending alerts to maintenance people, or change PLC parameters. It can also control other downstream devices via input and output (I/O) connections when certain conditions are met, so controllers using different protocols can exchange data.
Then the rest, the cleared data, is sent to the cloud. This saves dataflow and bandwidth and relieves the cloud from excessive load.
3. Upload data to the cloud
Today’s world is increasingly data driven. As the core part of the IIoT ecosystem, the cloud plays a major role in centralized management, data analytics and decision making.
Just as data-collecting devices differ in communication protocols, different clouds vary in connection and interaction methods. For instance, major public clouds such as Microsoft Azure and AWS from Amazon are connected with software development kits (SDKs). Interaction logic between clouds and requested functions from the edge also differ. Therefore, sending data to the cloud means a lot of work in integrating the gateway and the cloud.
A cloud gateway enables system integrators to connect to the cloud with ease, and most users require custom interaction with the cloud to upload data. As technology advances, today’s cloud gateway often supports major IoT clouds. It only takes a few steps to configure the cloud so data can travel from the source to the cloud.
While system integrators seek to monitor everything from the cloud to ensure their systems work properly, manufacturers need to manage factories via supervisory control and data acquisition (SCADA) systems. Thus, the gateway enables local SCADA systems to acquire data via industrial protocols and the cloud via message queuing telemetry transport (MQTT) communications.
4. Implement digital projects
It takes time to get fully digitalized. Starting a new project often involves quite a bit of work: to prepare all the devices, integrate them, program your applications, etc. In a fast-moving world, time is everything.
A cloud and edge solution should be easy for deployment and configuration so new projects can be implemented as soon as possible. As more management tools emerge, those gateways can be managed from a cloud platform. Web configuration is supported, and the configuration can be imported and exported. Deployment and batch management can be done on the platform.
To meet ever changing business demand and respond to new requirements as projects progress, customization becomes necessary. For instance, the cloud platform needs different support from the gateway in its iteration; as data analysis deepens, some data processing logic on the edge needs to be adjusted.
Cloud and edge design delivers better user experiences
The cloud and the edge are working very close in the IIoT. It’s possible to make better use of the edge through efficient coordination and give the user a better understanding of what’s going on in the field, ensure devices are working efficiently, to deliver a better user experience. With a more efficient and sounder database, better insights are available for product improvement and parameter optimization, which can enhance competitiveness in the Industry 4.0 era.
KEYWORDS: Industrial cloud and edge advice, Engineers’ Choice Awards
How are you using edge and cloud architectures to improve operations?