CyberVille 2.0: Establishes basis for self-learning industrial IoT networks

Finland-based open source standards CyberLightning Ltd. has announced the release of version 2.0 of the CyberVille software platform, which provides a “see it at a glance” view, advanced analytics and functional control of the complex sensor and machine networks that comprise the Internet of Everything (IoE).

Organisations can implement systems that learn from the collected data and operating inputs of smart nodes and various network layers, with the addition of edge-device functionality and support for independent yet connected instances of the application.

The new release meant the CyberVille platform could now be deployed on low-cost embedded computing edge devices, dedicated servers/private clouds, and data center scale Clouds.

This scalable, edge-to-Cloud intelligence, said the company, came with several related benefits:

– Improved IoE network efficiency based on screening and use of data collected at the local level that is not needed for operations beyond the local Site

– Self-managing local networks that can be connected to create one or more chains of intelligence between families of devices, systems and subnetworks

– Common APIs, user interface and data handling between each instance of the platform, which allows organisations to access specific device groups and manage local activity across a CyberVille IoE network

Chief Executive Officer of CyberLightning Ville Mickelsson said the new release marked an important step in evolving from connected, but highly centralised data systems to an architecture that is the basis of a neural network for the IoE.

Introduced in May 2014, the CyberVille software platform integrates heterogeneous data and inputs from multiple control systems to create a unified view and control panel for complex networks that can be accessed on any client device, from smart phones and Tablets to traditional desktops.

It is based on open-source, standards based Internet technology, and provides a multilayered 3D view of complex networks based on a combination of geographic information system (GIS) data sets and 3D models, along with all of the real time data feeds associated with the various objects that make up the networks under management.

Image Credit: CyberLightning

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