View source for Johnson Controls Tyco IP Holdings LLP (20240345551). BUILDING MANAGEMENT SYSTEM WITH NATURAL LANGUAGE MODEL-BASED DATA STRUCTURE GENERATION simplified abstract

=BUILDING MANAGEMENT SYSTEM WITH NATURAL LANGUAGE MODEL-BASED DATA STRUCTURE GENERATION=


==Organization Name==

[[:Category:Johnson Controls Tyco IP Holdings LLP|Johnson Controls Tyco IP Holdings LLP]]


[[Category:Johnson Controls Tyco IP Holdings LLP]]

==Inventor(s)==

[[:Category:Rajiv Ramanasankaran of San Jose CA (US)|Rajiv Ramanasankaran of San Jose CA (US)]][[Category:Rajiv Ramanasankaran of San Jose CA (US)]]

[[:Category:Krishnamurthy Selvaraj of Milwaukee WI (US)|Krishnamurthy Selvaraj of Milwaukee WI (US)]][[Category:Krishnamurthy Selvaraj of Milwaukee WI (US)]]

==BUILDING MANAGEMENT SYSTEM WITH NATURAL LANGUAGE MODEL-BASED DATA STRUCTURE GENERATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240345551 titled 'BUILDING MANAGEMENT SYSTEM WITH NATURAL LANGUAGE MODEL-BASED DATA STRUCTURE GENERATION

'''Simplified Explanation:'''
The patent application describes a method for building management systems that use language model-based data structure generation. This method involves selecting data sources based on natural or semantic language queries and applying machine learning models to generate outputs.

* Key Features and Innovation:
    - Utilizes natural language queries for selecting data sources in building management systems.
    - Incorporates machine learning models to generate outputs based on the queries.
    - Training data includes sample data and metadata from various data sources.

* Potential Applications:
    - Building management systems in commercial buildings.
    - Smart home automation systems.
    - Industrial control systems.

* Problems Solved:
    - Simplifies the process of selecting data sources in building management systems.
    - Enhances the efficiency of data retrieval and analysis.
    - Improves the user experience by using natural language queries.

* Benefits:
    - Streamlines data management processes.
    - Increases the accuracy of data selection.
    - Enhances the overall functionality of building management systems.

* Commercial Applications:
    - Optimizing energy usage in commercial buildings.
    - Enhancing security systems in smart homes.
    - Improving operational efficiency in industrial settings.

* Prior Art:
    - Further research can be conducted on similar methods used in data management systems and machine learning applications.

* Frequently Updated Research:
    - Stay updated on advancements in natural language processing and machine learning technologies for building management systems.

'''Questions about Building Management Systems with Language Model-Based Data Structure Generation:'''

1. How does the use of natural language queries improve the selection of data sources in building management systems?
2. What are the potential challenges in implementing machine learning models for data structure generation in building management systems?


==Original Abstract Submitted==

systems and methods are disclosed relating to building management systems with language model-based data structure generation. for example, a method can include receiving a query to select, from a plurality of data sources of a building management system, a selected one or more data sources according to a characteristic indicated by the query in at least one of a natural language representation or a semantic representation. the method can further include applying the query as input to a machine learning model to cause the machine learning model to generate an output indicating the selected one or more data sources, the machine learning model configured using training data comprising sample data and metadata from the plurality of data sources. the method can further include presenting, using at least one of a display device or an audio output device, the output.



[[Category:G05B13/02]]
[[Category:G06F16/248]]
[[Category:G06N3/0895]]
[[Category:CPC_G05B13/027]]