Platforms

6 Edge Capabilities Critical to IoT Systems Management

October 1, 2024

Estimated reading time: 4 minutes

IoT systems empower industrial enterprises to improve productivity and transform critical business processes. However, implementation presents unique challenges for enterprise organizations.

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Person holding a smartphone with digital icons representing "Digital Transformation" and symbols for automation, RPA, AI and edge capabilities connected in a network pattern.

For successful IoT adoption, enterprises need to take a systems approach. This approach creates pathways for data to flow from edge to cloud. This data can be collected, processed, rationalized and integrated with other business systems.

For example, an organization might start by considering its IoT business applications, including:

  • Next-generation connected machines and factories
  • Manufacturing execution systems
  • Factory information systems
  • SCADA

Everything below these applications is part of an IoT system that manages the complexity of connecting and managing devices. It also orchestrates the data that feeds each business application.

Today’s IoT technology requires operations and IT teams to rethink business and technology outcomes. Meanwhile, they must remember that data from IoT deployments is almost certain to change enterprise business processes.

Therefore, organizations must understand the technology requirements for an IoT systems approach before choosing their platform. This article will look at the edge capabilities you need in an IoT platform and how they will help your IoT systems succeed.

6 IoT Platform Edge Capabilities

1. AI at the Edge Revolutionizes Industrial Processes

A person interacts with a digital tablet in front of robotic arms and industrial machinery, with overlaid graphics displaying various technological and engineering data.

Incorporating artificial intelligence (AI) into the industrial Internet of Things (IIoT) can enhance product quality and minimize inspection errors. Moreover, you can improve the standard of manufactured goods by incorporating well-trained AI models in your IoT solution. This will help you increase customer satisfaction and remain competitive.

AI at the edge should support multiple industrial applications, including:

  • Classification
  • Object and anomaly detection
  • Distance measurement

Managers need access to this real-time IoT data and analytics through a user-friendly interface.

2. Data Orchestration Capabilities Start at the Edge

Close-up of a blue circuit board with various digital icons representing the edge capabilities of IoT and industrial automation.

When you can process data near its source (e.g., the factory floor), it eliminates the need to pass machine data back to the cloud. This edge processing capability allows enterprises to gain value from their real-time machine data and minimizes:

  • Network utilization
  • Data transfer
  • Storage costs

Many systems filter data at the edge and send to the cloud only what is needed to inform business systems and processes. This two-pronged approach to data processing and orchestration improves efficiency and reduces operational costs.

3. Out-of-the-Box Bidirectional Connectors

A complex industrial system with large green pipes and interconnected technology icons.

An out-of-the-box bidirectional integration framework at the edge allows enterprises to integrate modern and legacy equipment. At the same time, it reduces the need for custom coding.

Enterprises should also look for an IoT platform provider that supports several connectivity protocols, such as Modbus and Profibus. These integrative capabilities allow businesses to continue using legacy equipment alongside newer machines like connected robots, saving time and money.

4. Remote Management for Edge Devices

A man is using a tablet to control a robot.

Rich device management capabilities allow you to remotely manage and monitor edge devices, including modifications. Some platforms with remote management for edge devices also use over-the-air (OTA) mechanisms to allow firmware upgrades to:

  • Patch security exploits
  • Deliver bug fixes
  • Add new features

These capabilities allow operations teams to respond quickly and efficiently to any issues while maintaining high levels of security.

5. Self-Contained Edge Nodes

A self-contained edge node is integrated with the cloud but can operate as a separate entity. It addresses issues that arise from unreliable or intermittent connectivity. With self-contained edge nodes, a lack of connectivity will not impact on-premises operations, minimizing downtime. This edge capability ensures secure, reliable data delivery.

6. Enterprise Integration for Edge Capabilities

Enterprise integration is a unique IoT platform edge capability. With enterprise-grade software in your back office, you can map real-time data from your platform to enterprise IoT applications. This functionality allows you to create M2M solutions with vendor-neutral enterprise applications.

A holistic approach to building an IoT solution means looking beyond devices, data orchestration and processing at the edge. While the edge system is crucial, it’s part of a larger whole. When delivered to other systems, such as AI models and ERPs, the data can improve process efficiencies and empower leaders to make informed decisions.

Speak with our IIoT experts to discover what an IoT platform with edge capabilities can do for your enterprise.

Editor’s Note: This blog was originally published on 6 July 2017 and has since been updated.