Edge Intelligence is helping Industrial Internet of Things (IIoT) systems process data instantaneously and closer to the source of the data, thereby reducing latency and communication costs.

Equipping the IIoT Edge Devices with Cloud Intelligence

A new computing model that helps create autonomous edge nodes is changing the IIoT landscape. Edge nodes are data-aggregation points in an IIoT system where the physical world of the sensors and actuators interacts with computational resources such as IIoT gateway computers. This new computing model is based on edge nodes that are strengthened with local storage and computing power and enhanced with machine-learning algorithms that enable them to process data locally and make quick process-related decisions. An intelligent edge node:

. Enables faster decisions in accordance with local identity management and access control policies
. Secures data close to its source
. Reduces communication costs

Edge intelligence is edge computing fortified with machine-learning or self-learning algorithms, advanced networking capabilities, and end-to-end security. Here, we discuss four key elements of a good edge intelligence solution.

1. Localized Data Processing

The troves of data collected at the edge of a network can quickly lose their relevance. Hence, the data should be processed and useful insights derived from it at the earliest. Mission-critical systems, such as healthcare and factory monitoring, require quality data measurements and instant decisions. In addition to being time-consuming, sending data from the edge to the cloud can lead to data corruption and processed data without the required context. For these reasons, the edge node should be equipped with the ability to process data locally, and only key information should be sent to the cloud to develop data models. Edge nodes with local storage and processing capabilities keep the data closer to the source.

2. Real-Time Decision-Making at the Edge

Edge intelligence enables real-time decision-making at the edge nodes. Decision latency can be drastically reduced by enabling edge node analytics. Machine-learning or self-learning algorithms can be developed locally or in the cloud and deployed at the edge to make the edge nodes autonomous, enabling quick decision-making.

3. Robust Edge-to-Node Communication

Data integrity is a key in the edge-computing model because key decisions are made at the edge-node level. Data that is sensed and measured at the edge devices is of little use if the communication between the devices and the edge node is not consistent. No data loss or data corruption can be tolerated as the edge node is now responsible for making key process-related decisions. Other communication aspects to consider are range, bandwidth, device-to-device communication, the communication protocols to support, and how to power edge devices. A good edge network is one that is optimized for wireless sensor communication.

4. Secure Edge

The life cycle of an IIoT system is often longer than a traditional computing system. Most of the edge devices continue to be in operation even decades after they have been deployed. While servers and PCs are complex enough to allow for security provisions, IIoT nodes are usually low in power consumption and processing power. Edge-intelligence solutions equip the edge node with local storage and processing power. Close on the heels of these developments comes a varied set of software and hardware solutions that helps secure the edge devices and nodes. Some of the methods used to secure the edge nodes are end-to-end security encryption, intrusion prevention systems (IPS), and external hardware security using a trusted platform module (TPM). Because the edge nodes are the gateway to the physical world, when an edge device or node is compromised, it is not just data that is at risk. Cyberattackers can now potentially access unsecure edge nodes and devices to interfere with industrial processes or shut down equipment, resulting in financial losses and life-threatening situations.

067_cloud-iiot-edge-gateway-modbus-aws-w1200.pngMoxa’s Solution

Moxa’s IIoT Edge Gateway family consists of cloud-ready edge computers that are optimized for IIoT applications to enable robust, secure data processing and transmission. To learn more about Moxa’s cloud-ready IIoT Edge Gateways visit our website.

To download our white paper on edge intelligence click here.

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