Method and system for automatically supplementing a data stream received from a building management system to assist substance access, aggregation

Abstract

A data stream (14) comprising a stream of point values is received from a BMS (16). For each of the one or more point values of the data stream (14), one or more point markers based at least in part on the point type of the respective point value are inserted into the data stream (14), thereby producing a supplemental data stream. A selected one of the point values of the supplemental data stream is identified with reference to the one or more point markers in the supplemental data stream. An aggregation flag is inserted into the supplemental data stream, where the aggregation flag includes an aggregation flag value that is an aggregation of point values of selected ones of the point values of the supplemental data stream. At least some of the supplemental data streams including the aggregated flag value are displayed on a display.

Description

Technical Field

[0001] The present disclosure relates to systems and methods for processing data streams received from a building management system, and more particularly to systems and methods for automatically supplementing data streams received from a building management system to facilitate subsequent access, aggregation, analysis, and display of data from the data streams. Background Art

[0002] With the migration of traditional building management systems (BMS) to the cloud and the application of big data analysis, traditional BMS systems are facing challenges from customers. These challenges can include how to quickly establish big data stream analysis based on the common requirements of BMS cloud applications, and how to effectively normalize the data required by big data engines from different subsystems. Most traditional BMS systems are deployed as a monolithic architecture on a single site, where each BMS system only serves one customer or one building, making the data volume small. BMS cloud applications focus more on analyzing data not only from building automation equipment but also from other enterprise applications, such as real-time alarm statistics, daily energy consumption, monthly energy consumption, and real-time passenger flow statistics, which need to be aggregated in batches or through streaming.

[0003] An important part of big data analysis is how to model and normalize data based on business needs, i.e., pre-processing of data. Since data comes from different subsystems, they have different naming conventions, use different communication protocols and / or APIs, etc. Therefore, it may be a challenge to design a flexible extract / transform / load (ETL) tool for receiving data from heterogeneous sources and normalizing them to meet the needs of BMS cloud applications. What is desired is a system and method for processing data streams received from a building management system, including automatically supplementing data streams to facilitate subsequent access and display of data from the data streams. Summary of the invention

[0004] The present disclosure relates to systems and methods for processing data streams received from a building management system, and more particularly to systems and methods for automatically supplementing data streams received from a building management system to facilitate subsequent access and display of data from the data streams.

[0005] An example can be found in a method for supplementing a data stream received from a building management system (BMS). The illustrative method includes receiving a data stream from a BMS, wherein the data stream includes a stream of point values ​​for each of a plurality of point types. At least some of the point values ​​have corresponding timestamps. One or more point markers are inserted into the data stream for each of the one or more point values ​​of the data stream. Each of the one or more point markers is based at least in part on the point type of the corresponding point value, thereby generating a supplemental data stream. Selected point values ​​of the point values ​​of the supplemental data stream are identified by reference to the one or more point markers in the supplemental data stream. An aggregate marker is inserted into the supplemental data stream, wherein the aggregate marker includes an aggregate marker value, which is an aggregation of point values ​​of selected point values ​​of the point values ​​of the supplemental data stream. At least some of the supplemental data streams including the aggregate marker value are displayed on a display.

[0006] Another example may be found in a method for supplementing a data stream received from a building management system (BMS) to facilitate subsequent access and display of data from the data stream. The illustrative method includes receiving a data stream from the BMS. One or more data tags are inserted into the data stream, thereby generating a supplemented data stream. Each of the one or more data tags may be associated with a corresponding data element in the data stream. An output data stream is determined based at least in part on data elements of the supplemented data stream that share a common data tag. The output data stream may be displayed on a display.

[0007] Another example can be found in a system including an input for receiving a data stream from a BMS and a controller operatively coupled to the input. The controller is configured to insert one or more data tags into the data stream, thereby generating a supplemental data stream. Each of the one or more data tags is associated with a corresponding data element in the data stream. The controller is configured to determine an output data stream based at least in part on data elements of the supplemental data stream that share a common data tag, and to send the output data stream to a display for display.

[0008] The above summary is provided to facilitate understanding of some features of the present disclosure, but is not intended to be a complete description. A comprehensive understanding of the present disclosure can be obtained by taking the entire specification, claims, drawings and abstract as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The present disclosure may be more fully understood by considering the following description of various exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, in which:

[0010] Figure 1 is a schematic block diagram of an exemplary system;

[0011] Figure 2is a flow chart illustrating an exemplary method for supplementing a data stream received from a BMS system;

[0012] Figure 3 is a flow chart illustrating an exemplary method for supplementing a data stream received from a BMS system;

[0013] Figure 4A and Figure 4B are flow charts that together illustrate exemplary methods for supplementing a data stream received from a BMS system;

[0014] Figure 5 is a flow chart illustrating an exemplary method for supplementing a data stream received from a BMS system;

[0015] Figure 6 is a flow chart illustrating an exemplary method for supplementing a data stream received from a BMS system;

[0016] Figure 7 is a schematic block diagram of an exemplary architecture;

[0017] Figure 8 is a schematic block diagram of an exemplary implementation workflow; and

[0018] Figures 9 to 11 is a screenshot showing an example of a selected widget for displaying selected data in a supplemental data stream.

[0019] Although the present disclosure is subject to various modifications and alternative forms, the details thereof have been shown by way of example in the accompanying drawings and will be described in detail. However, it should be understood that it is not intended to limit the aspects of the present disclosure to the specific exemplary embodiments described. On the contrary, it is intended to cover all modifications, equivalents and alternatives that fall within the spirit and scope of the present disclosure. DETAILED DESCRIPTION

[0020] The following description should be read with reference to the accompanying drawings, in which the same reference numerals indicate the same elements. The accompanying drawings are not necessarily drawn to scale and are not intended to limit the scope of the present disclosure. In some figures, elements that are not necessary for understanding the relationship between the illustrated components may have been omitted for clarity.

[0021] It is assumed herein that all numbers are modified by the term "about" unless the content clearly dictates otherwise. The recitation of numerical ranges by endpoints includes all numbers subsumed within that range (eg, 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and 5).

[0022] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. As used in this specification and the appended claims, the term "or" is generally employed in its sense including "and / or" unless the content clearly dictates otherwise.

[0023] It should be noted that references in the specification to "an embodiment," "some embodiments," "other embodiments," etc. indicate that the described embodiments may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, these phrases are not necessarily referring to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in conjunction with an embodiment, it is contemplated that the feature, structure, or characteristic may apply to other embodiments, whether or not explicitly described, unless otherwise explicitly stated to the contrary.

[0024] Figure 1 1 is a schematic block diagram of an exemplary system 10. The exemplary system 10 includes an input 12 for receiving a data stream 14 from a BMS 16. A controller 18 is operably coupled to the input 12. The controller 18 is configured to insert one or more data tags into the data stream, thereby generating a supplemental data stream, each of the one or more data tags being associated with a corresponding data element in the data stream. The controller 18 is configured to determine an output data stream 20 based at least in part on data elements of the supplemental data stream that share a common data tag. The controller 18 is configured to send the output data stream 20 to a display 24 via an output 22 for display.

[0025] In some cases, the controller 18 may be configured to insert an aggregate tag into the supplemental data stream, wherein the aggregate tag includes an aggregate tag value that represents an aggregation of one or more data elements of the supplemental data stream that share a common data tag. In some cases, the output data stream 20 may include the aggregate tag. In some cases, the controller 18 may be configured to receive user input via a user interface 26, wherein the user input at least partially defines a widget, including identifying a common data tag. The user interface 26 may be separate from the display 24. For example, the display 24 may be part of the user interface 26. In some cases, the widget references the common data tag and determines the output data stream 20 based at least in part on the data elements of the supplemental data stream that share the common data tag.

[0026] Figure 2is a flow chart illustrating an exemplary method 30 for supplementing a data stream, such as data stream 14, received from a building management system (BMS), such as BMS 16. Method 30 includes receiving a data stream from the BMS, wherein the data stream includes a stream of point values ​​for each of a plurality of point types, at least some of the point values ​​having corresponding timestamps, as indicated by block 32.

[0027] In some cases, the data stream is real-time. The real-time data stream need not be delivered immediately after the BMS generates the point value of the data stream. For example, the real-time data stream may include some delays, such as processing and communication delays, before being delivered to the system 10. It is contemplated that the delay of the real-time data stream may be up to 15 minutes, up to 10 minutes, up to 5 minutes, up to 1 minute, up to 5 seconds, or less.

[0028] One or more point tags are inserted into the data stream for each of the one or more point values ​​of the data stream. Each of the one or more point tags is based at least in part on the point type of the corresponding point value, thereby generating a supplemental data stream, as shown in box 34. For example, the point type corresponding to power consumption can be marked with point tags such as {point role: "electricity"}, {interval: "900"}, {total}, and {consumption}. These are merely example point tags. In some cases, method 30 includes inserting multiple point tags into the data stream for each of the one or more point values ​​of the data stream. Each of the multiple point tags can be based at least in part on the point type of the corresponding point value, and in some cases based on the hierarchical structure level of the corresponding point value within the BMS (e.g., within a hierarchical structure model of the BMS).

[0029] One or more point tags in the supplementary data stream are referenced to identify a selected point value in the point values ​​of the supplementary data stream, as shown in box 36. An aggregate tag may be inserted into the supplementary data stream, wherein the aggregate tag includes an aggregate tag value that is a point value aggregation of the selected point values ​​in the point values ​​of the supplementary data stream, as shown in box 38. In some cases, the aggregate tag value of the aggregate tag includes a point value aggregation of the selected point values ​​in the point values ​​of the supplementary data stream within a predetermined time period. For example, the aggregate tag value of the aggregate tag may include an aggregation of point values ​​​​tagged with all {point role: "electricity"}, {total}, and {consumption} within a predetermined time period identified by the timestamp tag of the point value. In this example, the aggregate tag value may represent the total electricity consumption within the predetermined time period. The aggregate tag with the aggregate tag value is then inserted into the supplementary data stream. In some cases, the aggregate tag value of the aggregate tag may include a point value aggregation of the selected point values ​​in the point values ​​of the supplementary data stream at a predetermined hierarchical structure level and / or multiple predetermined hierarchical structure levels of the BMS.

[0030] In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include the sum of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period. The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, year-over-year differences in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream. In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include consecutive time period differences in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream (e.g., month-over-month). The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, an average, mean, or standard deviation of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period.

[0031] At least some of the supplementary data streams including the aggregated tag values ​​are then displayed on a display, as shown in block 40. In some cases, the data stream is received from the BMS in real time, and the supplementary data stream is generated in real time. One or more point tags may include a group tag, wherein the group tag is associated with corresponding point values ​​sharing the same group tag. In some cases, one or more point tags may include a topic tag, wherein the topic tag is associated with corresponding point values ​​of the data stream sharing the same topic tag. Various different tags can be used for different groupings of associated point values, sometimes in a hierarchical manner.

[0032] Figure 34 is a flow chart illustrating an exemplary method 42 for supplementing a data stream (such as data stream 14) received from a building management system (BMS) (such as BMS 16). The exemplary method 42 includes receiving a data stream from the BMS, wherein the data stream includes a stream of point values ​​for each of a plurality of point types, at least some of the point values ​​having corresponding timestamps, as shown in block 44. One or more point markers are inserted into the data stream for each of the one or more point values ​​of the data stream. Each of the one or more point markers may be based at least in part on the point type of the corresponding point value, thereby generating a supplemented data stream, as shown in block 46. In some cases, the method 42 includes inserting a plurality of point markers into the data stream for each of the one or more point values ​​of the data stream. Each of the plurality of point markers may be based at least in part on the point type of the corresponding point value and on a hierarchical level of the corresponding point value within a hierarchy (e.g., a hierarchy model) of the BMS.

[0033] The selected one of the point values ​​of the supplemental data stream is identified with reference to one or more point tags in the supplemental data stream, as shown in block 48. An aggregate tag may be inserted into the supplemental data stream, wherein the aggregate tag includes an aggregate tag value that is an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream, as shown in block 50. In some cases, the aggregate tag value of the aggregate tag includes an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream over a predetermined time period. In some cases, the aggregate tag value of the aggregate tag may include an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream at a predetermined hierarchical structure level and / or a plurality of predetermined hierarchical structure levels of the BMS.

[0034] In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include the sum of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period. The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, year-on-year differences in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream. In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include consecutive time period differences (month-on-month) in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream. The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, an average, mean, or standard deviation of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period.

[0035] At least some of the supplemental data streams including aggregated tag values ​​are displayed on a display, as shown in box 52. In some cases, the data stream is received from the BMS in real time and the supplemental data stream is generated in real time. One or more point tags may include a group tag, wherein the group tag is associated with corresponding point values ​​sharing the same group tag. One or more point tags may include a topic tag, wherein the topic tag is associated with corresponding point values ​​of the data stream sharing the same topic tag. Various different tags can be used for different groupings of associated point values, sometimes in a hierarchical manner.

[0036] In some cases, the method 42 may also include storing the hierarchical model of the BMS, as indicated at block 54. One or more point markers may be inserted into the data stream for each of the one or more point values ​​of the data stream, wherein at least some of the one or more point markers identify a hierarchical level of the corresponding point value within the hierarchical model of the BMS, as indicated at block 56.

[0037] Figure 4A and Figure 4B 1 is a flow chart that together illustrates an exemplary method 58 for supplementing a data stream (such as data stream 14) received from a building management system (BMS) (such as BMS 16). The exemplary method 58 includes receiving a data stream from the BMS, wherein the data stream includes a stream of point values ​​for each of a plurality of point types, at least some of the point values ​​having corresponding timestamps, as shown in block 60. One or more point markers are inserted into the data stream for each of the one or more point values ​​of the data stream. Each of the one or more point markers may be based at least in part on the point type of the corresponding point value, thereby generating a supplemented data stream, as shown in block 62. In some cases, the method 58 includes inserting a plurality of point markers into the data stream for each of the one or more point values ​​of the data stream, wherein at least some of the plurality of point markers are based at least in part on the point type of the corresponding point value and a hierarchical level of the corresponding point value within a hierarchical model of the BMS.

[0038] The one or more point tags in the supplemental data stream are then referenced to identify a selected one of the point values ​​of the supplemental data stream, as shown in block 64. An aggregate tag is inserted into the supplemental data stream, wherein the aggregate tag includes an aggregate tag value that is an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream, as shown in block 66. In some cases, the aggregate tag value of the aggregate tag includes an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream over a predetermined time period. In some cases, the aggregate tag value of the aggregate tag may include an aggregation of point values ​​of the selected one of the point values ​​of the supplemental data stream at a predetermined hierarchical structure level and / or multiple predetermined hierarchical structure levels of the BMS.

[0039] In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include the sum of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period. The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, year-over-year differences in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream. In some cases, the point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include consecutive time period differences in the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream (e.g., month-over-month). The point value aggregation of selected point values ​​in the point values ​​of the supplemental data stream may include, for example, an average, mean, or standard deviation of the point values ​​of the selected point values ​​in the point values ​​of the supplemental data stream over a predetermined time period.

[0040] Method 58 Figure 4B Continuing, at least some of the supplemental data streams including aggregated tag values ​​are displayed on a display, as shown in block 68. In some cases, the data streams are received from the BMS in real time, and the supplemental data streams are implemented in real time. One or more point tags may include a group tag, wherein the group tag is associated with corresponding point values ​​sharing the same group tag. One or more point tags may include a topic tag, wherein the topic tag is associated with corresponding point values ​​of the data stream sharing the same topic tag. Various different tags can be used for different groupings of associated point values, sometimes in a hierarchical manner.

[0041] The method 58 may also include receiving a configuration setting from a user via a user interface. The configuration setting configures one or more display elements (e.g., widgets) of the display to reference the aggregate tag, as shown in block 70. The aggregate tag referenced by the one or more display elements is then identified in the supplemental data stream, as shown in block 72. In some cases, the method 58 may include displaying an aggregate tag value of the aggregate tag referenced by the one or more display elements on the display, as shown in block 74.

[0042] Figure 5is a flow chart showing an illustrative method 76 for supplementing a data stream (such as data stream 14) received from a building management system (BMS) (such as BMS 16) to facilitate subsequent access and display of data from the data stream. The method 76 includes receiving a data stream from the BMS, as shown in block 78. Inserting one or more data tags into the data stream, thereby generating a supplemental data stream, each of the one or more data tags being associated with a corresponding data element in the data stream, as shown in block 80. Determining an output data stream based at least in part on data elements of the supplemental data stream that share a common data tag, as shown in block 82. Displaying the output data stream on a display, as shown in block 84. In some cases, determining the output data stream includes inserting an aggregate tag into the supplemental data stream, wherein the aggregate tag includes an aggregate tag value that represents an aggregation of one or more data elements of the supplemental data stream that share a common data tag. In some cases, the output data stream includes the aggregate tag.

[0043] Figure 6 8 is a flow chart showing an exemplary method 86 for supplementing a data stream (such as data stream 14) received from a building management system (BMS) (such as BMS 16) to facilitate subsequent access and display of data from the data stream. The method 86 includes receiving a data stream from the BMS, as shown in block 88. Inserting one or more data tags into the data stream, thereby generating a supplemental data stream, each of the one or more data tags being associated with a corresponding data element in the data stream, as shown in block 90. ​​Determining an output data stream based at least in part on data elements of the supplemental data stream that share one or more common data tags, as shown in block 92. Displaying the output data stream on a display, as shown in block 94. In some cases, determining the output data stream includes inserting an aggregate tag into the supplemental data stream, wherein the aggregate tag includes an aggregate tag value that represents an aggregation of one or more data elements of the supplemental data stream that share one or more common data tags. In some cases, the output data stream includes the aggregate tag.

[0044] In some cases, the method 86 may also include defining a widget to be displayed on the display, wherein the widget references the one or more common data tags, and wherein the widget is configured to determine an output data stream and display the output data stream, as shown in block 96. In some cases, the method 86 may also include receiving user input via a user interface, wherein the user input at least partially defines the widget, including identifying the one or more common data tags, as shown in block 98.

[0045] Figure 71 is a schematic block diagram of an exemplary architecture 100. The exemplary architecture 100 includes a data extractor 102 configured to extract data from a plurality of BMS sites 104 (respectively labeled 104a, 104b, 104c to 104n). The data extractor 102 may extract data from any number of different sites. In some cases, the data extractor 102 inserts one or more point tags into the data stream extracted from the BMS site 104 to produce a supplemental data stream. The point tag may be based at least in part on the point type of the corresponding point. The data extractor 102 may also insert tags that indicate the hierarchical structure of the point in the overall hierarchical structure of the BMS system (including the various BMS sites 104 in this example). The tags to be inserted may be defined by a facility hierarchical structure block 132, which may be configured using a configuration tool 130. The data extractor 102 places the resulting supplemental data stream into a Kafka (open source distributed event streaming platform) 106 topic stream, which is then provided to a stream analytics engine framework 108.

[0046] The supplemental data stream with the inserted markers is provided to a stream analytics engine framework 108 including a stream analytics engine 110. The stream analytics engine 110 may include one or more calculators such as, but not limited to, a yearly alarm count calculator 112, a monthly energy consumption calculator 114, a daily visitor count calculator 116, and a visitor count YOY (year-over-year) calculator 118. These are examples only. It is contemplated that the stream analytics engine 110 may include a variety of different calculators, depending on the desired application.

[0047] The stream analysis engine framework 108 refers to the tags in the supplementary data stream provided by Kafka 106 to identify appropriate point values ​​in the supplementary data stream for processing by each of the various calculators 112, 114, 116, and 118. Each of the calculators 112, 114, 116, and 118 can calculate the aggregation of one or more point values ​​of the supplementary data stream provided by Kafka 106 that share one or more corresponding public data tags. Each of the calculators 112, 114, 116, and 118 can insert the corresponding aggregate tag into the supplementary data stream, wherein the aggregate tag includes the calculated aggregate tag value. The stream analysis engine framework 108 outputs the resulting supplementary data stream to the analysis result block 120. The tag tool 122 provides tags that may have been used in the supplementary data stream for reference. The result flows to the public data source API 124. In some cases, the tag group block 126 provides the available tags to the business intelligence (BI) presentation block 128.

[0048] Figure 8134. The exemplary specific implementation workflow 134 includes a data extractor block 136, which can be regarded as an example of a data extractor 102. The data extractor block 136 includes an input terminal 138 that receives information from a database 140 and a BMS 142. The transformation block 144 outputs to an output terminal 146 and a facility tag model 148. The data extractor block 136 outputs to a Kafka stream block 150 together. An example of data output is shown in 152. In this embodiment, the data extractor block 136 has added tags to the data stream. For example, the point type corresponding to electricity consumption has been marked with point tags {pointrole: "electricity"}, {interval: "900"}, {total} and {consumption}. These are just example point tags. The data extractor block 136 can also normalize the point value to a common format, and remove and / or correct outliers and / or missing data in some cases.

[0049] In the example workflow, Kafka stream block 150 communicates with Flink calculator 152 including Kafka consumer 154. The consumed data is mapped to each location via the inserted tags, as shown in block 156. For example, the data is keyed by the location tag, as shown in block 158. The daily consumption is determined at block 160, and the daily consumption is aggregated into a daily total consumption at block 162. The data is output to Cassandra 166, as shown in block 164. Cassandra 166 reports to data query block 168, as does facility tag model 170. Data query block 168 outputs to dashboard 172. An example of the calculation results is shown in 174.

[0050] In some cases, all or part of a dashboard may be defined using display elements such as widgets. Step one is to select the location of one or more widgets on the dashboard. Fig. 9 As shown in the example in , step two includes selecting a widget from multiple widget types. Fig. 9 Screen 176 is shown including multiple widget types such as, but not limited to, trends, gauges, horizontal bars, etc. Screen 176 includes a "Next" button 178 that can be used to select one or more selected widget types and a "Cancel" button 180 that can be selected to cancel. Fig.10 , step three includes selecting tags as the data source for the selected widget. Fig.10 Screen 182 is shown, which includes a widget name entry 184, a data source entry 186, and a display format entry 188. The data source entry 186 may list one or more tags that have been added to the supplemental data stream. Screen 182 includes an "OK" button 190 that can be selected to accept the information entered and a selectable button 191 that can be selected to return to a previous screen (such as Fig. 9 176) of the screen shown in FIG. Fig.11 As shown in the example in , step four is to select the widget style. Fig.11 Screen 194 is shown, which includes a widget name entry 196, a data source entry 198, and a widget style entry 200. Screen 194 includes an "OK" button 202 that can be selected to accept the information entered and a selectable button 204 that can be selected to return to the previous screen (such as Fig.10 182) of the screen shown in FIG.

[0051] Those skilled in the art will recognize that the present disclosure may be embodied in various forms other than the specific embodiments described and contemplated herein. Therefore, changes in form and details may be made without departing from the scope and spirit of the present disclosure as described in the appended claims.

Claims

1. A method for supplementing a data stream received from a building management system (BMS), the method comprising: receiving the data stream from the BMS, wherein the data stream includes a stream of point values ​​for each of a plurality of point types, at least some of the point values ​​having corresponding timestamps; inserting one or more point markers into the data stream for each of the one or more point values ​​of the data stream, each of the one or more point markers being based at least in part on the point type of the corresponding point value, thereby generating a supplemental data stream; identifying a selected one of the point values ​​of the supplemental data stream by reference to the one or more point markers in the supplemental data stream; inserting an aggregate marker into the supplemental data stream, wherein the aggregate marker comprises an aggregate marker value that is a point value aggregation of the selected ones of the point values ​​of the supplemental data stream; as well as At least some of the supplementary data streams including the aggregated marking value are displayed on a display. 2 . The method according to claim 1 , wherein the data stream is received from the BMS in real time, and the inserting step, the referencing step, the inserting step, and the displaying step are performed in real time.

3. The method according to claim 1, further comprising: Storing a hierarchical structure model of the BMS; as well as One or more point markers are inserted into the data stream for each of the one or more point values ​​of the data stream, wherein at least some of the one or more point markers identify a hierarchical level of the corresponding point value within the hierarchical model of the BMS.

4. The method according to claim 1, comprising: Inserting a plurality of point tags into the data stream for each of one or more of the point values ​​of the data stream, each of the plurality of point tags being based at least in part on the point type of the corresponding point value and a hierarchical level of the corresponding point value within a hierarchical model of the BMS. 5 . The method of claim 1 , wherein the aggregate tag value of the aggregate tag comprises a point value aggregation of the selected point values ​​among the point values ​​of the supplemental data streams within a predetermined time period.

6. The method of claim 1 , wherein the aggregate tag value of the aggregate tag comprises a point value aggregation of the selected point values ​​among the point values ​​of the supplemental data streams at a predetermined hierarchical level and / or a plurality of predetermined hierarchical levels of the BMS.

7. The method of claim 1, wherein the point value aggregation of the selected ones of the point values ​​of the supplemental data stream comprises summing the point values ​​of the selected ones of the point values ​​of the supplemental data stream over a predetermined time period.

8. The method of claim 1, wherein the point value aggregation of the selected ones of the point values ​​of the supplemental data stream comprises a year-over-year difference in point value of the selected ones of the point values ​​of the supplemental data stream.

9. The method of claim 1, wherein the point value aggregation of the selected ones of the point values ​​of the supplemental data stream comprises consecutive time period differences in point values ​​of the selected ones of the point values ​​of the supplemental data stream.

10. The method of claim 1, wherein the point value aggregate of the selected ones of the point values ​​of the supplemental data stream comprises a point value average, mean, or standard deviation of the selected ones of the point values ​​of the supplemental data stream over a predetermined time period.

11. The method of claim 1 , wherein one or more of the point tags include a group tag, wherein the group tag is associated with the corresponding point values ​​sharing the same group tag.

12. The method of claim 1, wherein one or more of the point tags include a topic tag, wherein the topic tag is associated with the corresponding point values ​​of the data streams sharing the same topic tag.

13. The method according to claim 1, further comprising: receiving, via a user interface, a configuration setting from a user, the configuration setting configuring one or more display elements of the display to reference the aggregate indicia; identifying, in the data stream, the aggregate tag referenced by the one or more display elements; as well as The aggregate indicia value of the aggregate indicia referenced by the one or more display elements is displayed on the display.

14. A method for supplementing a data stream received from a building management system (BMS) to facilitate subsequent access and display of data from the data stream, the method comprising: receiving the data stream from the BMS; inserting one or more data markers into the data stream, thereby generating a supplemental data stream, each of the one or more data markers being associated with a corresponding data element in the data stream; determining an output data stream based at least in part on data elements of the supplemental data stream that share a common data tag; as well as The output data stream is displayed on a display.

15. The method of claim 14, wherein determining the output data stream comprises: inserting an aggregate marker into the supplemental data stream, wherein the aggregate marker comprises an aggregate marker value representing an aggregation of one or more data elements of the supplemental data stream that share the common data marker; and The output data stream includes the aggregation tag.

16. The method according to claim 14, further comprising: A widget is defined to be displayed on the display, wherein the widget references the common data tag, and wherein the widget is configured to perform the determining step and the displaying step.

17. The method according to claim 16, further comprising: User input is received via a user interface, wherein the user input at least partially defines the widget, including identifying the common data tag.

18. A system comprising: An input terminal, the input terminal being used to receive a data stream from the BMS; a controller operatively coupled to the input, the controller configured to: inserting one or more data markers into the data stream, thereby generating a supplemental data stream, each of the one or more data markers being associated with a corresponding data element in the data stream; determining an output data stream based at least in part on data elements of the supplemental data stream that share a common data tag; as well as The output data stream is sent to a display for display.

19. The system of claim 18, wherein the controller is configured to: inserting an aggregate marker into the supplemental data stream, wherein the aggregate marker comprises an aggregate marker value representing an aggregation of one or more data elements of the supplemental data stream that share the common data marker; and The output data stream includes the aggregation tag.

20. The system of claim 18, wherein the controller is configured to: receiving user input via a user interface, wherein the user input at least partially defines the widget, including identifying the common data tag; and The widget references the common data tag and determines the output data stream based at least in part on data elements of the supplemental data stream that share the common data tag.

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