System and method for benchmarking environmental data

• US 9,390,391 B2
• Filed: 05/31/2013
• Issued: 07/12/2016
• Est. Priority Date: 09/15/2011
• Status: Active Grant

• Current Assignee: Zerofootprint Software Inc.
• Original Assignee: Zerofootprint Software Inc.
• Inventors: Dembo, Ron
• Primary Examiner(s): Beutel, William
• Application Number:
  US13/907,021
• Publication Number:
  US 20130268325A1
• Time in Patent Office: 1,138 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems

Abstract

Systems and methods for benchmarking collected or computed environmental data for one or more entities. The systems and methods involve determining a distribution for historical environmental data for the entity, collecting current environmental data for the entity, and generating, using the processor, a graphical representation benchmarking the current environmental data against the historical environmental data, wherein the graphical representation comprises the data segments and represents the current environmental data at a position within one of the segments, where the data segments are calculated using the distribution.

Claims

1. A method for generating and updating a graphical user interface for continuous real-time or near real-time benchmarking of environmental data for an entity, wherein the method is implemented by a processor and a storage device storing instructions, the instructions being executable to configure the processor to perform operations comprising:

determining an approximate normal distribution for historical environmental data for the entity by estimating a mean and a standard deviation, wherein the historical environmental data comprise a plurality of historical data values, wherein each of the plurality of historical data values is associated with a time interval for a historical date;

generating, using the processor, a graphical representation of data segments, the data segments being approximately equal in size when displayed as part of a graphical user interface, wherein the data segments are generated based on the approximate normal distribution of the historical environmental data, the mean and the standard deviation, wherein the data segments represent a scale of environment values as they compare to the estimated mean, each data segment providing boundaries along the scale of environmental values and representing a different range of environmental values, wherein a first data segment represents an average consumption with a first range of data values along the scale, a second data segment represents a less than average consumption with a second range of data values along the scale, and a third data segment represents a greater than average consumption with a third range of data values along the scale, the first range of data values, the second range of data values and the third range of data values being different even though the data segments are approximately equal in size when displayed as part of the graphical user interface such that more common data values are spread out along the scale and less common data values are compacted along the scale;

collecting real-time or near real-time environmental data for the entity to continuously receive a real-time data value associated with the time interval for a real-time date;

generating, using the processor, the graphical user interface for display on a device, wherein the graphical user display comprises a graphical representation benchmarking the real-time or near real-time environmental data against the historical environmental data, wherein the graphical representation illustrates the data segments as approximately equal in size and represents the real-time or near real-time environmental data as a graphical element indicator at a position on the scale within one of the data segments to represent how the real-time data value compares to the estimated mean for the distribution of the historical environmental data in order to benchmark the real-time or near real-time environmental data against the historical environmental data;

continuously collecting additional real-time or near real-time environmental data for the entity to receive real-time updates as additional real-time data values associated with the time interval for the real-time date; and

continuously updating the graphical representation based on the additional real-time or near real-time environmental data to move the graphical element indicator to different positions along the scale for the data segments to indicate the how the additional real-time data values associated with the time interval compare to the estimated mean in order to provide a continuously real-time or near real-time benchmark against the historical environmental data.

2. The method of claim 1, wherein the historical and real-time or near real-time environmental data relate to resource consumption by the entity and wherein the plurality of historical data values and the real-time data value comprises consumption values.

3. The method of claim 1, wherein the historical and real-time or near real-time environmental data relate to emission generation by the entity and wherein the plurality of historical data values and the real-time data value comprises emission activity data.

4. The method of claim 1, wherein the historical and real-time or near real-time environmental data is associated with a data type and a location of the environmental data.

5. The method of claim 1, wherein the historical and real-time or near real-time environmental data is associated with a data type and a location of the environmental data.

6. The method of claim 1, wherein the first data segment represents environmental data within the approximate range X(t′

)<

μ

−

(0.491)σ

, the second data segment represents environmental data within the approximate range μ

−

(0.491)σ

<

X(t′

)<

μ

+(0.491)σ

, and the third data segment represents environmental data within the approximate range X(t′

)>

μ

+(0.491)σ

, where X(t′

) is an environmental data point, μ

is the estimated mean, and σ

is the estimated standard deviation.

7. The method of claim 1, wherein determining the distribution for the historical environmental data for the entity comprises determining an empirical distribution for the historical environmental data.

21. A non-transitory computer-readable medium upon which a plurality of instructions are stored, the instructions for performing the steps of the method as claimed in claim 1.

8. A method for generating and updating a graphical user interface for continuous real-time or near real-time benchmarking environmental data for an entity, wherein the method is implemented by a processor and a storage device storing instructions, the instructions being executable to configure the processor to perform operations comprising:

a) for each of a plurality of time intervals,

determining an approximate normal distribution for historical environmental data for the entity by estimating a mean and a standard deviation, wherein the historical environmental data comprises a plurality of historical data values, wherein each of the plurality of historical data values is associated with the respective time interval for a historical date;

collecting real-time or near real-time environmental data for the entity, wherein the real-time or near real-time environmental data comprises a real-time data value for the respective time interval; and

generating, using the processor, a graphical representation of time interval specific data segments for the respective time interval, the data segments being approximately equal in size when displayed as part of a graphical user interface, wherein the time interval specific segments are generated based on the approximate normal distribution of the historical environmental data, the mean and the standard deviation, wherein the data segments represent a scale of environment values as they compare to the estimated mean, each data segment providing boundaries along the scale of environmental values and representing a different range of environmental values, wherein a first data segment represents an average consumption with a first range of data values along the scale, a second data segment represents a less than average consumption with a second range of data values along the scale, and a third data segment represents a greater than average consumption with a third range of data values along the scale, the first range of data values, the second range of data values and the third range of data values being different even though the data segments are approximately equal in size when displayed as part of the graphical user interface such that more common data values are spread out along the scale and less common data values are compacted along the scale;

collecting real-time or near real-time environmental data for the entity to continuously receive a real-time data value associated with the time interval for a real-time date;

determining a position representing the real-time or near real-time environmental data within one of the time interval specific data segments for benchmarking the real-time or near real-time environmental data against the historical environmental data;

continuously collecting additional real-time or near real-time environmental data for the entity to receive real-time updates as additional real-time data values associated with the time interval for the real-time date;

b) generating, using the processor, the graphical user interface for display on a device, wherein the graphical user display comprises a graphical representation benchmarking the real-time or near real-time environmental data for all of the plurality of time intervals against the historical environmental data for all of the plurality of time intervals, wherein the graphical representation illustrates overall data segments as being approximately equal in size and representing the scale of environment values as they compare to the estimated mean for all of the plurality of time intervals, wherein the graphical representation represents, for each of the plurality of time intervals, real-time or near real-time environmental data of the respective time interval as a graphical element indicator at a position on the scale within one of the overall data segments to represent how the real-time data value compares to the estimated mean for the distribution of the historical environmental data in order to benchmark the real-time or near real-time environmental data against the historical environmental data; and

c) continuously updating the graphical representation based on the additional real-time or near real-time environmental data to move the graphical element indicator to different positions along the scale for the overall data segments to indicate the how the additional real-time data values associated with the time interval compare to the estimated mean in order to provide a continuously real-time or near real-time benchmark against the historical environmental data.

9. The method of claim 8, wherein the historical and real-time or near real-time environmental data relate to resource consumption by the entity and wherein the plurality of historical data values and the real-time data value comprises consumption values.

10. The method of claim 8, wherein the historical and real-time or near real-time environmental data relate to emission generation by the entity and wherein the plurality of historical data values and the real-time data value comprises emission activity data.

11. The method of claim 8, wherein, for each of the plurality of time intervals, the position representing the real-time or near real-time environmental data for the respective time interval indicates how the real-time or near real-time environmental data for the respective time interval compares to an estimated mean of the distribution of the historical environmental data for the respective time interval.

12. The method of claim 8, wherein the overall data segments and the time interval specific data segments for each of the plurality of time intervals comprise a first overall data segment representing a lower than average, a second overall data segment representing an average, and a third overall data segment representing a higher than average.

13. The method of claim 8, wherein the overall data segments and the time interval specific data segments for each of the plurality of time intervals comprise a first overall data segment, a second overall data segment and a third overall data segment, wherein the first overall data segment represents environmental data within the range X(t′

)<

μ

−

(0.491)σ

, the second overall data segment represents environmental data within the range μ

−

(0.491)σ

<

X(t′

)<

μ

+(0.491)σ

, and the third overall data segment represents environmental activity data within the range X(t′

)>

μ

+(0.491)σ

, where X(t′

) is an environmental data point, μ

is the estimated mean, and σ

is the estimated standard deviation.

14. The method of claim 8, wherein determining the distribution for the historical environmental data for the entity comprises determining an empirical distribution for the historical environmental data.

15. A system for generating and updating a graphical user interface for continuous real-time or near real-time benchmarking environmental data for an entity, wherein the system comprises a processor and a storage device storing instructions, the instructions being executable to configure the processor to:

a) determine an approximate normal distribution for historical environmental data for the entity by estimating a mean and a standard deviation, wherein the historical environmental data comprise a plurality of historical data values, wherein each of the plurality of data consumption values is associated with a time interval for a historical date;

generating, using the processor, a graphical representation of data segments, the data segments being approximately equal in size when displayed as part of a graphical user interface, wherein the data segments are generated using the approximate normal distribution for the historical environmental data, the mean and the standard deviation, wherein the data segments represent a scale of environment values as they compare to the estimated mean, each data segment providing boundaries along the scale of environmental values and representing a different range of environmental values, wherein a first data segment represents an average consumption with a first range of data values along the scale, a second data segment represents a less than average consumption with a second range of data values along the scale, and a third data segment represents a greater than average consumption with a third range of data values along the scale, the first range of data values, the second range of data values and the third range of data values being different even though the data segments are approximately equal in size when displayed as part of the graphical user interface such that more common data values are spread out along the scale and less common data values are compacted along the scale;

collecting real-time or near real-time environmental data for the entity to continuously receive a real-time data value associated with the time interval for a real-time date;

generate, using the processor, the graphical user interface for display on a device, wherein the graphical user display comprises a graphical representation benchmarking the real-time or near real-time environmental data against the historical environmental data, wherein the graphical representation illustrates the data segments as approximately equal in size and represents the real-time or near real-time environmental data as a graphical element indicator at a position on the scale within one of the segments to represent how the real-time data value compares to the estimated mean for the distribution of the historical environmental data in order to benchmark the real-time or near real-time environmental data against the historical environmental data;

continuously collect additional real-time or near real-time environmental data for the entity to receive real-time updates as additional real-time data values associated with the time interval for the real-time date; and

continuously update the graphical representation based on the additional real-time or near real-time environmental data to move the graphical element indicator to different positions along the scale for the data segments to indicate the how the additional real-time data values associated with the time interval compare to the estimated mean in order to provide a continuously real-time or near real-time benchmark against the historical environmental data.

16. The system of claim 15, wherein the historical and real-time or near real-time environmental data relate to resource consumption by the entity and wherein the plurality of historical data values and the real-time data value comprises consumption values.

17. The system of claim 15, wherein the historical and real-time or near real-time environmental data relate to emission generation by the entity and wherein the plurality of historical data values and the real-time or near real-time data value comprises emission activity data.

18. The system of claim 15, wherein the historical and real-time or near real-time environmental data is associated with a data type and a location.

19. The system of claim 15, wherein the first data segment represents environmental data within the approximate range X(t′

)<

μ

−

(0.491)σ

, the second data segment represents environmental data within the approximate range μ

−

(0.491)σ

<

X(t′

)<

μ

+(0.491)σ

, and the third data segment represents environmental data within the approximate range X(t′

)>

μ

+(0.491)σ

, where X(t′

) is an environmental data point, μ

is the estimated mean, and σ

is the estimated standard deviation.

20. The system of claim 15, wherein the processor is configured to determine the distribution for the historical environmental data for the entity by determining an empirical distribution for the historical environmental data.