Method and Device of Predicting the Level of Customer Amount, and Method and System of Controlling Temperature of Aircondiction by Using the Same

• US 20100114401A1
• Filed: 10/14/2009
• Published: 05/06/2010
• Est. Priority Date: 11/06/2008
• Status: Abandoned Application

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Lin, Cheng-Ting, Tseng, Wen-Hsiang
• Application Number:
  US12/578,985
• Publication Number:
  US 20100114401A1
• Time in Patent Office: Days
• US Class Current: 700/300
• CPC Class Codes: B60H 1/00742 by detection of the vehicle occupants' presence; by detection of conditions relating to the body of occupants, e.g. using radiant heat detectors
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2110/12 of the outside air
• CPC Class Codes: F24F 2120/10 Occupancy
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

A method of predicting the level of customer amount is provided. The method at least comprises the steps of: (a) a counter counting person-time within a time period; (b) a processor checking whether a referenced customer amount of the time period is stored in a database if being at the beginning of the time period; and (c) the processor estimating the level of customer amount according to the referenced customer amount of the time period if the referenced customer amount of the time period is stored in a database.

Claims

1. A method of predicting the level of customer amount, the method comprising:

a counter counting the person-time within a time period;

a processor checking whether a referenced customer amount of the time period is stored in a database if being at the beginning of the time period; and

the processor estimating the level of customer amount according to the referenced customer amount if the referenced customer amount of the time period is stored in the database.

2. The method according to claim 1, wherein a time cycle comprises N time periods, when the database at least contains N items of referenced customer amount of the time cycle, the processor taking the average value of the first n largest items of referenced customer amount of the N items of referenced customer amount as a maximum customer amount, both n and N are a positive integer, and the customer amount is graded by the processor according to the proportion of the referenced customer amount to the maximum customer amount.

3. The method according to claim 2 further comprising:

the processor estimating the level of customer amount as high level if the referenced customer amount approximately is larger than 70% of the maximum customer amount;

the processor estimating the level of customer amount as middle level if the referenced customer amount approximately ranges 35%˜

70% of the maximum customer amount;

the processor estimating the level of customer amount as low level if the referenced customer amount approximately is smaller than 35% of the maximum customer amount.

4. The method according to claim 1 further comprising:

the processor setting the level of customer amount as high level if the referenced customer amount is not stored in the database.

5. The method according to claim 1 further comprising:

the processor predicting the level of customer amount according to the currently accumulated person-time if counting goes on for an estimating time.

6. The method according to claim 5, wherein the estimating time is approximately half of the time period.

7. The method according to claim 5, wherein the method of predicting the level of customer amount comprises:

the processor obtaining a predicted customer amount according to the currently accumulated person-time by an the estimation method; and

the processor calculating the level of customer amount according to the proportion of the predicted customer amount to the maximum customer amount.

8. The method according to claim 1 further comprising:

the counter accumulating the person-time within the time period as an actual customer amount if being at the end of the time period;

the counter storing the actual customer amount of the time period in the database and the processor updating the referenced customer amount of the time period therein.

9. The method according to claim 1, wherein the method of updating the referenced customer amount of the time period comprises:

the processor using the average value of the referenced customer amount and the actual customer amount of the time period as a referenced customer amount of the time period of the next time cycle.

10. A method of controlling aircondictioning temperature, the method comprising:

a measuring unit measuring the outdoor temperature of a time period;

a processor predicting the level of customer amount, comprising;

a counter counting the person-time within a time period;

the processor checking whether a referenced customer amount of the time period is stored in a database if being at the beginning of the time period; and

the processor estimating the level of customer amount according to the referenced customer amount if the referenced customer amount of the time period is stored in the database; and

the processor setting the airconditioning temperature according to the outdoor temperature of the time period and level of customer amount.

11. The method according to claim 10 further comprising:

the processor applying the outdoor temperature measured by the measuring unit to a corresponding relationship so as to obtain two set values of airconditioning temperature.

12. The method according to claim 11, wherein the step of setting airconditioning temperature comprises:

the processor setting the airconditioning temperature at the higher of the two set values of airconditioning temperature if the level of customer amount is at low level.

13. The method according to claim 11, wherein airconditioning temperature is set at the lower of the two set values of airconditioning temperature if the level of customer amount is at high level.

14. The method according to claim 11, wherein airconditioning temperature is set at the average value of the two set values of airconditioning temperature if the level of customer amount is at middle level.

15. The method according to claim 10, wherein a time cycle comprises N time periods, the database contains at least N items of referenced customer amount of the N time periods, the processor taking the average value of the first n largest items of referenced customer amount of the N items of referenced customer amount as a maximum customer amount, both n and N are a positive integer, and the customer amount is graded by the processor according to the proportion of the referenced customer amount to the maximum customer amount.

16. The method according to claim 15, wherein the step of predicting the level of customer amount further comprises:

the processor estimating the level of customer amount as high level if the referenced customer amount approximately is larger than 70% of the maximum customer amount.

the processor estimating the level of customer amount as middle level if the referenced customer amount approximately ranges 35%˜

70% of the maximum customer amount;

the processor estimating the level of customer amount as low level if the referenced customer amount approximately is smaller than 35% of the maximum customer amount.

17. The method according to claim 10 further comprising:

the processor setting the level of customer amount as high level if the referenced customer amount is not stored in the database.

18. The method according to claim 10 further comprising:

the processor predicting the level of customer amount according to the currently accumulated person-time if counting goes on for an estimating time.

19. The method according to claim 18, wherein the estimating time is approximately a half of the time period.

20. The method according to claim 18, wherein the method of predicting the level of customer amount comprises:

the processor obtaining a predicted customer amount according to the currently accumulated person-time by an estimation method; and

the processor calculating the level of customer amount according to the proportion of the predicted customer amount to the maximum customer amount.

21. The method according to claim 18 further comprising:

the counter accumulating the person-time within the time period as an actual customer amount if being at the end of the time period;

the counter storing the actual customer amount of the time period in the database and the processor updating the referenced customer amount of the time period therein.

22. The method according to claim 18, wherein the method of updating the referenced customer amount of the time period comprises:

the processor using the average value of the referenced customer amount and the actual customer amount of the time period as a referenced customer amount of the time period of the next time cycle.

23. A device of predicting the level of customer amount, comprising:

a counter, for counting the person-time within a time period;

a database, for storing a plurality of person-time and referenced customer amount; and

a processor for checking whether a referenced customer amount of the time period is stored in a database if being at the beginning of the time period, and the processor estimating the level of customer amount according to the referenced customer amount if the referenced customer amount of the time period is stored in the database.

24. A system of controlling aircondicting temperature, the system comprising:

a measuring unit for measuring the outdoor temperature of a time period;

a counter, for counting the person-time within a time period;

a database, for storing a plurality of person-time and referenced customer amount; and

a processor for checking whether a referenced customer amount of the time period is stored in a database if being at the beginning of the time period, and the processor estimating the level of customer amount according to the referenced customer amount if the referenced customer amount of the time period is stored in the database;

wherein the processor setting the aircondicting temperature according to the outdoor temperature of the time period and the level of customer amount.