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Edge Device

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What is an Edge Device?

In the age of IIOT (Industrial Internet of Things), more and more new technologies are being introduced that rely on the cloud. These tools are often used to gather and transmit data that is collected on local networks, and because local devices and the cloud do not always use the same protocol, an edge device is needed to serve as the gateway – or translator – between local and cloud devices. 

The edge device enables data to be transmitted from the local network to the cloud where it can then be used for deep analysis. 

What are the Capabilities of an Edge Computing Device?

Manufacturing plants are increasingly relying on IOT devices. Examples include sensors that monitor the entire assembly line and share data to a cloud-based system for analysis and insights that can help improve efficiency and productivity. The specific capabilities of edge devices that are useful for manufacturers include:

  • Data management – the devices can be trained to determine which data is important to keep and which can be discarded. This will prevent the storage of large datasets that are just taking up space but are unlikely to ever be used. 
  • Offline – if for some reason connectivity is lost, an edge device will save the information until the network connection is regained and then will transfer the data to the cloud.
  • Process complex events – it is not just simple data that an edge device can transfer from a local device to the cloud. When complex patterns are developed and recognized on the cloud, the edge device can also transmit that information back to the local network.  
  • Artificial Intelligence and Machine Learning – When edge devices are powered by AI and ML, they can empower manufacturers to get real-time information and insights leading to better decision-making.  

Pros and Cons of Edge Devices

  • An edge device makes it possible to monitor the machine availability and condition of the entire shop-floor, including legacy devices.
  • Accurate and streamlined monitoring and analyzing of data means early detection of anomalies that can be remedied before causing larger problems.
  • Allows for predictive and preventative maintenance which lowers maintenance costs and improves uptime and efficiency.
  • In some areas, especially those that are more rural and have fewer skilled IT workers, it can be difficult to find the people with the right skills to set up and manage edge computing devices.
  • Some edge devices may be more susceptible to potential hackers and other security breaches. 
  • It’s possible (although not very likely) for data to get lost once it’s been processed on the edge device rather than being stored on the cloud. 
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