Accelerating the
Industrial Internet of Things

Industrial Edge Computing

Industrial Edge Computing
Industrial Edge Computing
Industrial Edge Computing
Industrial Edge Computing
Industrial Edge Computing
Industrial Edge Computing
Industrial Edge Computing
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DESCRIPTION
Edge (fog) computing shifts computing applications, data, and services away from centralized servers to the extremes of a network. This enables analytics and knowledge generation to occur at the source of the data.
Industrial IoT companies face challenges turning machine data into business intelligence. Existing cloud-based technologies do not solve problems of data analytics, software deployment, or updates and security for remote devices. Edge or fog computing solves the problem of accessing large amounts of machine-generated data by processing data at the edge of the network and converting it into actionable, useful business information.

In an Intelligent Industrial Fog, software can be deployed at various points in the network to not only automate monitoring and control, but also to apply embedded intelligent agents that can adjust device behaviors in relation to ongoing performance variables, reduce running costs by reducing power consumption during off-cycles, or even detect imminent failures and notify technicians to perform preventative maintenance.

Companies use edge computing technologies to analyze the data locally, sending only most important data to a centralised cloud. This reduces data transmission and storage costs while also allowing real-time analysis and action. Edge computing also allows remote software deployment and secure M2M communication.

Edge computing leverages resources that are not continuously connected to a network, such as laptops, smartphones, tablets and sensors. It covers a wide range of technologies, from wireless sensor networks and mobile data acquisition to cooperative distributed peer-to-peer ad hoc networking and processing. Import IoT applications include remote cloud services, distributed data storage and retrieval, and self-healing networks.
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