View source for 17850744. SYSTEM AND METHOD FOR REDUCTION OF DATA TRANSMISSION IN DYNAMIC SYSTEMS USING INFERENCE MODEL simplified abstract (Dell Products L.P.)

=SYSTEM AND METHOD FOR REDUCTION OF DATA TRANSMISSION IN DYNAMIC SYSTEMS USING INFERENCE MODEL=


==Organization Name==

[[:Category:Dell Products L.P.|Dell Products L.P.]]


[[Category:Dell Products L.P.]]

==Inventor(s)==

[[:Category:Ofir Ezrielev of Be'er Sheva (IL)|Ofir Ezrielev of Be'er Sheva (IL)]][[Category:Ofir Ezrielev of Be'er Sheva (IL)]]

[[:Category:Jehuda Shemer of Kfar Saba (IL)|Jehuda Shemer of Kfar Saba (IL)]][[Category:Jehuda Shemer of Kfar Saba (IL)]]

==SYSTEM AND METHOD FOR REDUCTION OF DATA TRANSMISSION IN DYNAMIC SYSTEMS USING INFERENCE MODEL - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17850744 titled 'SYSTEM AND METHOD FOR REDUCTION OF DATA TRANSMISSION IN DYNAMIC SYSTEMS USING INFERENCE MODEL

==Simplified Explanation==

The patent application describes methods and systems for managing data collection by a data aggregator and data collector. These methods aim to reduce computing resources used for data aggregation by implementing a multi-stage data reduction process. Here are the key points:

* Data aggregation is performed by a data aggregator, which collects data from a data collector.
* To reduce the amount of data transmitted for aggregation, a multi-stage data reduction process is implemented.
* Twin inference models are used at both the data aggregator and data collector to identify relationships in the collected data.
* Feature relationship inference models are used to identify relationships in the collected data.
* A portion of the collected data is transmitted to the data aggregator, while a second portion is withheld based on an acceptable level of error.
* The withheld portion of the data is reconstructed at the data aggregator, including an acceptable level of error compared to the original data.

Potential applications of this technology:

* Data management and aggregation systems in various industries such as finance, healthcare, and manufacturing.
* Internet of Things (IoT) applications where large amounts of data need to be collected and aggregated.
* Research and analysis projects that require efficient data collection and aggregation.

Problems solved by this technology:

* Reduces the computing resources required for data aggregation by implementing a multi-stage data reduction process.
* Minimizes the amount of data transmitted for aggregation, reducing bandwidth and storage requirements.
* Improves efficiency and speed of data collection and aggregation processes.

Benefits of this technology:

* Saves computing resources and reduces costs associated with data aggregation.
* Increases efficiency and speed of data collection and aggregation processes.
* Enables more effective analysis and decision-making based on aggregated data.


==Original Abstract Submitted==

Methods and systems for managing data collection are disclosed. A data aggregator may aggregate data collected by a data collector. To reduce computing resources used for aggregation, the data aggregator and data collector may implement a multi-stage data reduction processes to reduce the quantity of data transmitted for data aggregation purposes. The multi-stage data reduction process may include implementing twin inference models at the aggregator and collector, identifying relationships in the data collected by the data collector using feature relationship inference models, transmitting a portion of the collected data to the data aggregator and withholding a second portion of the collected data based on acceptable level of error for use of the collected data, and reconstructing the withheld portion of the collected data at the aggregator. The reconstructed portion of the collected data may include the acceptable level of error when compared to a corresponding portion of the collected data.



[[Category:G06F3/06]]