SYSTEMS AND METHODS FOR PREDICTING BUILDING FAULTS USING MACHINE LEARNING

    公开(公告)号:US20230145448A1

    公开(公告)日:2023-05-11

    申请号:US17523567

    申请日:2021-11-10

    IPC分类号: G05B13/02 G06N5/04

    CPC分类号: G05B13/027 G06N5/04

    摘要: A method for predicting time periods in which faults are likely to occur for a piece of building equipment. The method includes receiving a plurality of measurements for one or more points that are associated with a piece of building equipment, the plurality of measurements measured during a first time period; executing a machine learning model using the plurality of measurements as an input to generate fault data for a plurality of time periods subsequent to the first time period; selecting a second time period from the plurality of time periods responsive to an assessment of the fault data for the plurality of time periods indicating a fault will likely occur in the piece of building equipment during the second time period of the plurality of time periods; and performing an automated action responsive to the selection of the second time period.

    Building control system using reinforcement learning

    公开(公告)号:US12013673B2

    公开(公告)日:2024-06-18

    申请号:US17537179

    申请日:2021-11-29

    IPC分类号: G05B19/042 G06N3/08 G06N5/022

    摘要: Sensorized commercial buildings are a rich target for building a new class of applications that improve operational and energy efficiency of building operations that take into account human activities. Such applications, however, rarely experience widespread adoption due to the lack of a common descriptive schema that would enable porting these applications and systems to different buildings. Our demo presents Brick [4], a uniform schema for representing metadata in buildings. Our schema defines a concrete ontology for sensors, subsystems and relationships among them, which enables portable applications. Using a web application, we will demonstrate real buildings that have been mapped to the Brick schema, and show application queries that extracts relevant metadata from these buildings. The attendees would be able to create example buildings and write their own queries.

    BUILDING CONTROL SYSTEM USING REINFORCEMENT LEARNING

    公开(公告)号:US20230168649A1

    公开(公告)日:2023-06-01

    申请号:US17537179

    申请日:2021-11-29

    IPC分类号: G05B19/042 G06N5/02 G06N3/08

    摘要: Sensorized commercial buildings are a rich target for building a new class of applications that improve operational and energy efficiency of building operations that take into account human activities. Such applications, however, rarely experience widespread adoption due to the lack of a common descriptive schema that would enable porting these applications and systems to different buildings. Our demo presents Brick [4], a uniform schema for representing metadata in buildings. Our schema defines a concrete ontology for sensors, subsystems and relationships among them, which enables portable applications. Using a web application, we will demonstrate real buildings that have been mapped to the Brick schema, and show application queries that extracts relevant metadata from these buildings. The attendees would be able to create example buildings and write their own queries.