Abstract: A system and method for securely training a model comprises including the algorithms of the model into a training module, and communicating the training module from a vendor computer system to a customer computer system. The training module is operated on the customer's computer system using the data from the customer, and a trained training module is achieved after operating the training module on the customer's computer system. The trained training module is used to initialize at least one additional module, which is communicated from the customer's computer system to the vendor's computer system, is used to score observations.

Abstract: A method of operating a computer device includes obtaining measurements of one or more conditions of a power grid component associated with the computer device. The computer device forecasts a future state of the one or more conditions of the power grid component associated with the computer device. The computer device communicates with other computer devices associated with other power grid components to negotiate a behavior of the power grid component associated with the computer device using the forecast.

Abstract: Technologies for dynamic forecasting, aggregation, and validation may include circuitry configured to collect data indicative of power flows at multiple locations in an electrical grid, to receive one or more parameters for generation of a customized forecast indicative of predicted power flows associated with one or more of the multiple locations over a defined time period, to select a subset of the collected data that satisfies the one or more parameters, to produce a model to predict power flows in the electrical grid associated with the one or more locations, to determine whether the model is validated by determining whether a predicted production of power minus predicted losses is within a predefined range of a predicted consumption of power at the one or more locations, and to produce the customized forecast of predicted power flows associated with the one or more locations for the defined time period.

Abstract: Illustrative embodiments of systems and methods for providing interoperability between multiple data providers and/or customers are disclosed. In some embodiments, a method may include receiving, by a first server, a second gateway associated with a second server, wherein the second gateway is configured to translate data into a second protocol associated with the second server; deploying, by the first server, the second gateway on the first server; receiving, by the first server, a first request for first data from the second server; transferring, by the first server in response to receiving the first request, the first data into the second gateway; and translating, by the second gateway, the first data into the second protocol.

Abstract: Technologies for decentralized fleet analytics are disclosed. In at least one embodiment, a local cloud service at a plant site builds a first machine learning model of one or more first streams of data associated with the plant site. The local cloud service sends the first machine learning model to a cloud service connected to the plant site and other plant sites. The local cloud service receives a second machine learning model from the cloud service. The second machine learning model is trained as a function of the first machine learning model and one or more machine learning models built by the other plant sites. The local cloud service updates the first machine learning model based on the second machine learning model.

Abstract: A method of operating a computer device includes obtaining measurements of one or more conditions of a power grid component associated with the computer device. The computer device forecasts a future state of the one or more conditions of the power grid component associated with the computer device. The computer device communicates with other computer devices associated with other power grid components to negotiate a behavior of the power grid component associated with the computer device using the forecast.

Abstract: Cyber security for a communications network can be enhanced with benchmarking, logging, and monitoring message transfer latencies between nodes to detect any changes in equipment or configuration due to unauthorized surveillance. In addition, the transfer of the messages between nodes is provided with cyber attack mitigation measures to be able to maintain operations even if encryption is compromised.

Abstract: Technologies for dynamic forecasting, aggregation, and validation may include circuitry configured to collect data indicative of power flows at multiple locations in an electrical grid, to receive one or more parameters for generation of a customized forecast indicative of predicted power flows associated with one or more of the multiple locations over a defined time period, to select a subset of the collected data that satisfies the one or more parameters, to produce a model to predict power flows in the electrical grid associated with the one or more locations, to determine whether the model is validated by determining whether a predicted production of power minus predicted losses is within a predefined range of a predicted consumption of power at the one or more locations, and to produce the customized forecast of predicted power flows associated with the one or more locations for the defined time period.

Abstract: A system and method for securely training a model comprises including the algorithms of the model into a training module, and communicating the training module from a vendor computer system to a customer computer system. The training module is operated on the customer's computer system using the data from the customer, and a trained training module is achieved after operating the training module on the customer's computer system. The trained training module is used to initialize at least one additional module, which is communicated from the customer's computer system to the vendor's computer system, is used to score observations.

Abstract: Illustrative embodiments of systems and methods for providing interoperability between multiple data providers and/or customers are disclosed. In some embodiments, a method may include receiving, by a first server, a second gateway associated with a second server, wherein the second gateway is configured to translate data into a second protocol associated with the second server; deploying, by the first server, the second gateway on the first server; receiving, by the first server, a first request for first data from the second server; transferring, by the first server in response to receiving the first request, the first data into the second gateway; and translating, by the second gateway, the first data into the second protocol.

Abstract: An industrial asset management system includes a data acquisition system configured to receive asset data associated with at least one industrial asset and to modify the data acquisition system to enable the continued receipt of asset data associated with the at least one industrial asset in response to a detection of an internal change at the data acquisition system by the data acquisition system and a data processing system communicatively coupled to the data acquisition system and configured to process the asset data received from the data acquisition system and to modify the data processing system for the continued processing of the asset data in response to a detection by the data processing system of an internal change at the data processing system or the data acquisition system.

Abstract: An industrial asset management system includes a data acquisition system configured to receive asset data associated with at least one industrial asset and to modify the data acquisition system to enable the continued receipt of asset data associated with the at least one industrial asset in response to a detection of an internal change at the data acquisition system by the data acquisition system and a data processing system communicatively coupled to the data acquisition system and configured to process the asset data received from the data acquisition system and to modify the data processing system for the continued processing of the asset data in response to a detection by the data processing system of an internal change at the data processing system or the data acquisition system.

Abstract: Methods, systems and apparatus for initiating actions in a healthcare environment are disclosed. Illustrative embodiments receive identification data from tags assigned to healthcare resources via local positioning sensors. The illustrative embodiments also determine proximity of the healthcare resources based upon the identification data received via local positioning sensors. The embodiments also determine that an event has occurred in response to the proximity of the healthcare resources satisfying a relational condition of the event that relates the healthcare resources, and the healthcare resources satisfying a status condition of the event. The embodiments further initiate an action associated with the event in response to determining that the event has occurred.