Find the hidden “DNA” in your AMR data….

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Smart meter data can expose waste that other tools do not even look for. George Catto will explain where traditional tools fail and show that AMR data can fill this gap by exploiting pattern recognition of waste characteristics found in the data.

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Find the hidden “DNA” in your AMR data.

The Energy Manager's Biggest Challenge?
1
Where to begin?

Now you can't manage what you have measured
You can’t manage what you can't measure....
220 meters
1,100 graphs

Why Automation is Key?
• Big Data cannot be interpreted by humans
• Interpretation takes skill and too much time
• Current Energy Management portals do not solve this
Pattern recognition is the answer
5

6
What is Data-mining ?
A
B
C
D
A, B, C, D are characteristics (both of criminals and of waste)

Key performance indicators (KPI)
7
Optimum
Start
Optimum
Stop
Dry
Cycling
Excessive
Boost

Pattern recognition of time clock control
8

Pattern recognition of time clock control
9

Idealised Heating Response to Outside Air
Temperature
10

Sites sorted by relative performance
11
Median
Unpredictable
Predictable
Weather
Response KPI

Weather response KPI
12
Best Worst
Tight Clustering Loose Clustering

13
Best Worst
Summer Turndown KPI
Summer Off Summer On

Some sites don’t change time clocks
15
FailedWorking

What we found
16
Retail Chain
KPI % £
Daylight Saving Time 2 20,000
Weather Response 16 170,000
Summer Turndown 3 30,000
Total 21 220,000

Scalable expertise provides:
• Immediate waste identification
• Ranked monetary priority
• Avoidance of speculative surveys
• Self-adaptive comfort and cost models
• Quantification of project impacts
• Productivity gains
17

Example Deliverables
• Remedial recommendations for action:
Plant refurbishment, Controls, Behavioural,
• KPI based league tables ranked by potential
• Tailored reporting scheduled or on-demand
• Automated forecast and budgeting
18

In Summary
• Productivity gains, actionable savings and CSR
benefits,
Only possible with AMR-DNA
19

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一比一原版(UMTC毕业证书)明尼苏达大学双城分校毕业证如何办理

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Find the hidden “DNA” in your AMR data….

1. Powered by Find the hidden “DNA” in your AMR data.

2. The Energy Manager's Biggest Challenge? 1 Where to begin?

3. Now you can't manage what you have measured You can’t manage what you can't measure.... 220 meters 1,100 graphs

4. The traditional approach 3

5. The Complex approach 4

6. Why Automation is Key? • Big Data cannot be interpreted by humans • Interpretation takes skill and too much time • Current Energy Management portals do not solve this Pattern recognition is the answer 5

7. 6 What is Data-mining ? A B C D A, B, C, D are characteristics (both of criminals and of waste)

8. Key performance indicators (KPI) 7 Optimum Start Optimum Stop Dry Cycling Excessive Boost

9. Pattern recognition of time clock control 8

10. Pattern recognition of time clock control 9

11. Idealised Heating Response to Outside Air Temperature 10

12. Sites sorted by relative performance 11 Median Unpredictable Predictable Weather Response KPI

13. Weather response KPI 12 Best Worst Tight Clustering Loose Clustering

14. 13 Best Worst Summer Turndown KPI Summer Off Summer On

15. Daylight Saving time overview 14

16. Some sites don’t change time clocks 15 FailedWorking

17. What we found 16 Retail Chain KPI % £ Daylight Saving Time 2 20,000 Weather Response 16 170,000 Summer Turndown 3 30,000 Total 21 220,000

18. Scalable expertise provides: • Immediate waste identification • Ranked monetary priority • Avoidance of speculative surveys • Self-adaptive comfort and cost models • Quantification of project impacts • Productivity gains 17

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20. In Summary • Productivity gains, actionable savings and CSR benefits, Only possible with AMR-DNA 19

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