Patent classifications
G05B2219/33334
SYSTEMS AND METHODS FOR BROADCASTING DATA AND DATA TAGS ASSOCIATED WITH AN INDUSTRIAL AUTOMATION SYSTEM
An industrial control system may receive data associated with at least one component within an industrial automation system. The industrial control system may then determine whether the data is associated with at least one of a plurality of data tags, such that the at least one of the plurality of data tags describes at least one characteristic of the data. The industrial control system may then broadcast the data and the at least one of the plurality of data tags in a data feed channel when the data is associated with the at least one of the plurality of data tags.
Systems and methods for broadcasting data and data tags associated with an industrial automation system
An industrial control system may receive data associated with at least one component within an industrial automation system. The industrial control system may then determine whether the data is associated with at least one of a plurality of data tags, such that the at least one of the plurality of data tags describes at least one characteristic of the data. The industrial control system may then broadcast the data and the at least one of the plurality of data tags in a data feed channel when the data is associated with the at least one of the plurality of data tags.
SYSTEMS AND METHODS FOR BALANCING LOADS IN AN INDUSTRIAL AUTOMATION SYSTEM
An industrial control system may receive processing information from at least two control systems associated with at least two components within an industrial automation system. The processing information may include a processing load value for each of the at least two control systems. The industrial control system may then distribute processing loads associated with the at least two control systems when a total processing load between the at least two control systems is unbalanced.
Methods and systems for determining recommendations based on real-time optimization of machine learning models
Methods and systems are described for improvements to the use of distributed computer networks. For example, conventional systems may rely on the distribution of network or application traffic across multiple servers and may maintain load balancers to maintain that distribution in an efficient manner. Each load balancer may sit between client devices and backend servers, receiving and then distributing incoming requests to any available server capable of fulfilling them. The load balancers may ensure that no one server is overworked based on the number of processing requests directed to that server, which could degrade performance.