Method and system for evaluating media-playing sets

• US 7,647,326 B2
• Filed: 01/29/2007
• Issued: 01/12/2010
• Est. Priority Date: 01/29/2007
• Status: Expired due to Fees

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Laboratories of America Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Gil, Fernando Amat, Shivaji-Rao, Vishnu Kumar
• Primary Examiner(s): Lee; Wilson
• Application Number:
  US11/699,893
• Publication Number:
  US 20080183705A1
• Time in Patent Office: 1,079 Days
• Field of Search: 707 8- 10, 707/202, 707/102, 707/104.1, 726/22, 726/23
• US Class Current: 1/1
• CPC Class Codes: H04N 17/004 for digital television systems
• CPC Class Codes: H04N 21/25833 involving client hardware characteristics, e.g. manufacturer, processing or storage capabilities allocation of resources considering hardware capabilities in multiprogramming arrangements G06F9/5044; allocation of resources considering software capabilities in multiprogramming arrangements G06F9/5055
• CPC Class Codes: H04N 21/4424 Monitoring of the internal components or processes of the client device, e.g. CPU or memory load, processing speed, timer, counter or percentage of the hard disk space used error monitoring in general G06F11/30; arrangements for monitoring conditions of receiving stations in broadcast systems H04H60/32; diagnosis, testing or measuring for television receivers H04N17/04
• CPC Class Codes: H04N 21/4665 involving classification methods, e.g. Decision trees
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38

Abstract

An exemplary method and system for evaluating media-playing sets evaluates the likelihood of a selected performance condition occurring in a subject set including based on source data automatically collected from a sample group of the sets, systematic analysis of this data to form a decision tree model revealing prescribed values for characteristic input parameters that are determined to best relate to the condition, and automated comparison of the respective parameter values of the subject set to these prescribed values in order to screen each subject set for the likelihood of the condition occurring within a specified timeframe, which screening can be repeated for different conditions and timeframes using different decision tree models.

Claims

1. A method for evaluating a likelihood of degradation of equipment in media-playing sets measured over at least one future interval, each set being characterized by a plurality of input parameters, each having respective value ranges, said method comprising the steps of:

(a) collecting data identifying for each member of a sample group of said sets whether a selected performance attribute of said equipment has degraded below a threshold;

(b) analyzing said data so as to relate said selected performance attribute to selected ones of said input parameters and, also, to selected values within their respective ranges of said selected ones of said input parameters;

(c) evaluating the likelihood of said selected performance attribute degrading below said threshold during a one of said at least one future interval in an individual one of said media-playing sets by detecting the respective values of at least those ones of said input parameters of said individual one of said media playing sets corresponding to said selected ones of said input parameters and comparing said respective values to said selected values; and

(d) remotely alerting a user of said individual one of said media-playing sets, through said individual one of said media-playing sets, of the evaluated said likelihood of said selected performance attribute degrading below said threshold during said one of said at least one future interval.

2. The method of claim 1 wherein said analyzing step includes developing a diagnostic algorithm expressible as a decision tree, said selected ones of said input parameters being represented by nodes on said tree and said selected values of said selected ones of said input parameters being represented by at least one branch extending from each node.

3. The method of claim 2 wherein said decision tree has a root node and branches leading away to other nodes, said selected ones of said input parameters being ranked beginning at said root node and continuing along said branches in order from that showing the strongest correlation with said selected performance attribute to that showing the weakest.

4. The method of claim 1 further including adapting said method to a plurality of media-playing sets dispersed over locations geographically remote from each other by providing a support site that communicates through a network connection with each media-playing set and remotely detecting said respective values of each set from said support site.

5. The method of claim 4 including regularly detecting said respective values of each set from said support site to identify changes in said respective values signaling an increased likelihood of said performance attribute occurring in at least one of said sets.

6. The method of claim 1 further including the steps of evaluating the likelihood of said selected performance attribute degrading below said threshold during a second one of said at least one future interval in said individual one of said media-playing sets and remotely alerting the user of said individual one of said media-playing sets, through said individual one of said media-playing sets, of the evaluated said likelihood of said selected performance attribute degrading below said threshold during said second one of said at least one future interval.

7. The method of claim 4 wherein said analyzing step includes developing a diagnostic algorithm expressible as a decision tree for use in said comparing step and updating said algorithm by modifying said decision tree whenever said support site detects said selected performance attribute has occurred in one of said plurality of media-playing sets.

8. A system for evaluating a likelihood of degradation of equipment in media-playing sets measured over at least one future interval, each set being characterized by a plurality of input parameters, each having respective value ranges, said system comprising:

(a) an incident database capable of recording data identifying for each member of a sample group of said sets whether a selected performance attribute of said equipment has degraded below a threshold;

(b) an analyzer capable of analyzing said data and relating said selected performance attribute to selected ones of said input parameters and, in particular, to selected values within their respective ranges of said selected ones of said input parameters;

(c) a diagnostic tool capable of evaluating the likelihood of said selected performance attribute degrading below said threshold during a one of said at least one future interval in an individual one of said media-playing by obtaining the respective values of at least those ones of said input parameters of said individual one of said media-playing sets corresponding to said selected ones of said input parameters and comparing said respective values to said selected values; and

(d) a communication tool capable of remotely alerting a user of said individual one of said media-playing sets, through said individual one of said media-playing sets, of the evaluated said likelihood of said selected performance attribute degrading below said threshold during said one of said at least one future interval.

9. The system of claim 8 wherein said analyzer, in performing the analyzing operation, develops a diagnostic algorithm expressible as a decision tree, said selected ones of said input parameters being represented by nodes on said tree and said selected values of said selected ones of said input parameters being represented by at least one branch extending from each node.

10. The system of claim 9 wherein said decision tree has a root node and branches leading away to other nodes, said selected ones of said input parameters being ranked beginning at said root node and continuing along said branches in order from that showing the strongest correlation with said selected performance condition to that showing the weakest.

11. The system of claim 8 further including a support site, a network adapter in each set enabling network connection to said support site despite a plurality of said sets being geographically dispersed remotely from each other, and a detector at said site for remotely detecting status information about each set including the respective values of said input parameters of each set.

12. The system of claim 11 wherein said detector regularly detects said respective values of each set from said support site to identify changes in said respective values signaling an increased likelihood of said performance condition occurring in at least one of said sets.

13. The system of claim 12 further including an alarm at said site for remotely alerting the user of said at least one of said sets where said increased likelihood of said performance condition occurring is deemed undesirable.

14. The system of claim 11 wherein said analyzer develops a diagnostic algorithm expressible as a decision tree for use by said diagnostic tool in said comparing operation and said algorithm is updated by said analyzer modifying said decision tree whenever said support site detects said selected performance condition has occurred in one of said plurality of media-playing sets.