April 23, 2015 - CyberLightning announced release 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). With the addition of edge-device functionality and support for independent yet connected instances of the application, organizations can implement systems that learn from the collected data and operating inputs of smart nodes and various network layers.
With release 2.0, the CyberVille platform can be deployed on low-cost embedded computing edge devices, dedicated servers/private clouds, and data center scale clouds. This scalable, edge-to-cloud intelligence has 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 organization to access specific device groups and manage local activity across a CyberVille IoE network.
For energy operations, such as a wind farm, the embedded controller on individual windmills may run CyberVille locally, which would feed data to a private cloud instance of CyberVille used by the system operator to manage all of its working sites. In turn, the windmill manufacturer could implement a cloud instance of CyberVille to aggregate and analyze data on its entire installed base across all system operators.
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. Based on open-source, standards based Internet technology, it 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 network or networks under management.