公开(公告)号：US20220317675A1

公开(公告)日：2022-10-06

申请号：US17218661

申请日：2021-03-31

Applicant: Johnson Controls Technology Company

Inventor： Priti Shinde ,  Deepak Uppal

IPC: G05B23/02 ,  G06N20/00

Abstract: A building management system including one or more memory devices and one or more processors, the one or more memory devices configured to store instructions to be executed on the one or more processors, the processors configured to generate a first predictive model using a machine learning technique and an operating data set based on one or more operating parameters associated with at least one of a plurality of BMS subsystems. The processors are further configured to store the first predictive model at a first time interval, to receive a prediction request from a user input at a second time interval following the first time interval, and to retrieve the first predictive model. The one or more processors are further configured execute the retrieved predictive model to generate a first prediction in response to the prediction request; and initiate an automated control response based on the first prediction.

公开(公告)号：US11859846B2

公开(公告)日：2024-01-02

申请号：US17318877

申请日：2021-05-12

Applicant: Johnson Controls Technology Company

Inventor： Priti Shinde ,  Kathiresan Rajagopal ,  Abu Bakr Khan ,  Young M. Lee

IPC: F24F11/63 ,  G05B19/042 ,  G06Q50/06 ,  G06N20/10

CPC classification number: F24F11/63 ,  G05B19/042 ,  G06N20/10 ,  G06Q50/06

Abstract: A heating, ventilation, and air conditioning (HVAC) fault prediction system for a building including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to receive HVAC data relating to a plurality of HVAC components, the HVAC data indicating performance of the plurality of HVAC components, generate, based on the received HVAC data, a univariate prediction model and a multivariate prediction model, generate, using the received HVAC data, one or more predicted operational parameters for the plurality of HVAC components corresponding to a future time period, and execute at least one of the univariate prediction model or the multivariate prediction model on the one or more predicted operational parameters to predict a HVAC fault associated with at least one of the plurality of HVAC components to occur during the future time period.

公开(公告)号：US12045048B2

公开(公告)日：2024-07-23

申请号：US17218661

申请日：2021-03-31

Applicant: Johnson Controls Technology Company

Inventor： Priti Shinde ,  Deepak Uppal

IPC: G05B23/02 ,  G06N20/00

CPC classification number: G05B23/0283 ,  G05B23/0216 ,  G05B23/024 ,  G06N20/00

Abstract: A building management system including one or more memory devices and one or more processors, the one or more memory devices configured to store instructions to be executed on the one or more processors, the processors configured to generate a first predictive model using a machine learning technique and an operating data set based on one or more operating parameters associated with at least one of a plurality of BMS subsystems. The processors are further configured to store the first predictive model at a first time interval, to receive a prediction request from a user input at a second time interval following the first time interval, and to retrieve the first predictive model. The one or more processors are further configured execute the retrieved predictive model to generate a first prediction in response to the prediction request; and initiate an automated control response based on the first prediction.