Building management system with nested stream generation

Patent metadata

Field	Value
Publication number	US-2024338002-A1
Application number	US-202418747298-A
Country	US
Kind code	A1
Filing date	Jun 18, 2024
Priority date	Feb 10, 2017
Publication date	Oct 10, 2024
Grant date	—

Abstract

A building management system (BMS) includes building equipment configured to provide samples of one or more data points in the building management system and a timeseries service. The timeseries service is configured to identify a first timeseries processing workflow that uses an input timeseries as an input and defines processing operations to be applied to the samples of the input timeseries, perform the processing operations defined by the first timeseries processing workflow to generate a first derived timeseries comprising a first set of derived timeseries samples, identify a second timeseries processing workflow that uses the first derived timeseries as an input and defines processing operations to be applied to the samples of the first derived timeseries, and perform the processing operations defined by the second timeseries processing workflow to generate a second derived timeseries comprising a second set of derived timeseries samples.

First claim

What is claimed is:

1 . A building system, comprising:
a directed acyclic graph (DAG) database storing a plurality of DAGs defining processing workflows; one or more non-transitory computer-readable media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to:
receive a time correlated data stream from a data source;
identify a DAG of the DAG database that uses the time correlated data stream as an input to derive a derived time correlated data stream by determining whether any of the plurality of DAGs stored in the DAG database use the time correlated data stream as an input, wherein the DAG defines one or more processing operations of a processing workflow to be applied to the time correlated data stream; and
generate the derived time correlated data stream based on the DAG and the time correlated data stream.

2 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
identify a second DAG of the DAG database that uses the derived time correlated data stream as an input to derive a second derived time correlated data stream by determining whether any of the plurality of DAGs stored in the DAG database use the derived time correlated data stream as an input, wherein the second DAG defines one or more processing operations of a second processing workflow to be applied to the derived time correlated data stream; and generate the second derived time correlated data stream based on the second DAG and the derived time correlated data stream.

3 . The building system of claim 1 , wherein the derived time correlated data stream is a timeseries.

4 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
store the derived time correlated data stream in a data stream database.

5 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
collect, from building equipment, samples of one or more data points of the building equipment; generate the time correlated data stream to include the samples; and generate the derived time correlated data stream according to the DAG by:
performing the one or more processing operations defined by the DAG on at least some of the samples to generate a set of derived samples; and
storing the set of derived samples in the time correlated data stream.

6 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
generate the derived time correlated data stream according to the processing workflow based on data received from building equipment, wherein the building equipment include at least one of a sensor, heating, ventilation, and air conditioning (HVAC) equipment, lighting equipment, access control equipment, or security equipment.

7 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
identify one or more other timeseries to be used as inputs to the DAG; and generate an enriched processing workflow comprising the DAG, an input time correlated data streams, and the one or more other timeseries.

8 . The building system of claim 1 , wherein the instructions cause the one or more processors to generate the derived time correlated data stream by:
transforming one or more samples of an input time correlated data streams into one or more samples of a first set of derived samples by applying the one or more samples of the input time correlated data streams as an input to the processing workflow of the DAG; and assembling the first set of derived samples to form the derived time correlated data stream.

9 . The building system of claim 1 , wherein the DAG defines a first timeseries processing workflow and one or more first processing operations of the DAG are timeseries processing operations;
wherein a second DAG of the plurality of DAGS defines a second timeseries processing workflow and the one or more processing operations of the second DAG are timeseries processing operations.

10 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
identify a second DAG of the plurality of DAGS that uses the derived time correlated data stream as an input, wherein the second DAG defines the one or more processing operations to be applied to samples of the derived time correlated data stream; and generate a second derived time correlated data stream by performing the one or more processing operations defined by the second DAG, the second derived time correlated data stream comprising a second set of derived samples.

11 . The building system of claim 1 , wherein the instructions cause the one or more processors to generate a second derived time correlated data stream by:
transforming one or more samples of a first set of derived samples of the derived time correlated data stream into one or more samples of a second set of derived samples by applying the one or more samples of the first set of derived samples as an input to a second DAG of the plurality of DAGS; and assembling the second set of derived samples to form the second derived time correlated data stream.

12 . A method, comprising:
storing, by one or more processing circuits, a plurality of directed acyclic graphs (DAGs) in a DAG database, the plurality of DAGs defining processing workflows; receiving, by the one or more processing circuits, a time correlated data stream from a data source; identifying, by the one or more processing circuits, a DAG of the DAG database that uses the time correlated data stream as an input to derive a derived time correlated data stream by determining whether any of the plurality of DAGs stored in the DAG database use the time correlated data stream as an input, wherein the DAG defines one or more processing operations of a processing workflow to be applied to the time correlated data stream; and generating, by the one or more processing circuits, the derived time correlated data stream based on the DAG and the time correlated data stream.

13 . The method of claim 12 , comprising:
identifying, by the one or more processing circuits, a second DAG of the DAG database that uses the derived time correlated data stream as an input to derive a second derived time correlated data stream by determining whether any of the plurality of DAGs stored in the DAG database use the derived time correlated data stream as an input, wherein the second DAG defines one or more processing operations of a second processing workflow to be applied to the derived time correlated data stream; and generating, by the one or more processing circuits, the second derived time correlated data stream based on the second DAG and the derived time correlated data stream.

14 . The method of claim 12 , comprising:
collecting, by the one or more processing circuits, from building equipment, samples of one or more data points of the building equipment; generating, by the one or more processing circuits, the time correlated data stream to include the samples; and generating, by the one or more processing circuits, the derived time correlated data stream according to the DAG by:
performing the one or more processing operations defined by the DAG on at least some of the samples to generate a set of derived samples; and
storing the set of derived samples in the time correlated data stream.

15 . The method of claim 12 , comprising:
generating, by the one or more processing circuits, the derived time correlated data stream according to the processing workflow based on data received from buildi

Assignees

• Johnson Controls Tech Co

Inventors

• Park Youngchoon
• Sinha Sudhi R
• Venkiteswaran Vaidhyanathan
• Paulson Erik S
• Chennupati Vijaya S

Classifications

• G05B23/0264

  Control of logging system, e.g. decision on which data to store; time-stamping measurements · CPC title

• G05B15/02 Primary

  electric · CPC title

• G06F16/2474

  Sequence data queries, e.g. querying versioned data · CPC title

• G06F16/9024

  Graphs; Linked lists (G06F16/9027 takes precedence) · CPC title

• G06F16/258

  Data format conversion from or to a database · CPC title