Abstract: The disclosure relates to a data analytics platform in which a linear pipeline processing framework may use an abstracted query language to define a data fusion pipeline assembly mechanism. More particularly, the linear pipeline processing framework may include various operator groups that work in conjunction to organize data entries that can have substantially disparate data types (e.g., text, binary, video, audio, etc.) into a single normalized stream such that one or more processing modules may perform type-specific data processing and feature extraction, normalize an output into a single stream, and finally render the different data types as a fused output.

Abstract: A method of monitoring and controlling network traffic within an industrial control system including receiving one or more data packets at a smart network switching system operating software-defined networking, analyzing the one or more data packets at a protocol level within a control plane of the software-defined networking, based on the analysis, determining whether the one or more data packets are authorized data packets, and forwarding a data packet of the one or more data packets to a destination device within a data plane of the software-defined networking upon determining that the data packet is an authorized data packet. The method further includes providing information related to the analysis of the one or more data packets to an out-of-band monitoring and control system for display to a user, and receiving a response communication from the out-of-band monitoring and control system indicating whether the one or more data packets are authorized data packets.

Abstract: The disclosure relates to a data analytics platform that may implement a pipeline hinting system in which various modules in a data analytics pipeline can inform one another about module capabilities, condensing functions, temporal restrictions, decision-making information, etc. to determine whether to pass constituent data or aggregate data. The pipeline hinting system may therefore provide a substantially modular methodology to enable complex pipeline analytics that are transparent to a human because foreknowledge regarding the underlying data is not required. Instead, module capabilities may be used to dynamically create an appropriate data flow based on module ordering within the data analytics pipeline and the data that each module is configured to operate on.

Abstract: The disclosure relates to a data analytics platform in which a linear pipeline processing framework may use an abstracted query language to define a data fusion pipeline assembly mechanism. More particularly, the linear pipeline processing framework may include various operator groups that work in conjunction to organize data entries that can have substantially disparate data types (e.g., text, binary, video, audio, etc.) into a single normalized stream such that one or more processing modules may perform type-specific data processing and feature extraction, normalize an output into a single stream, and finally render the different data types as a fused output.