Human presence detection

Patent metadata

Field	Value
Publication number	US-9268390-B2
Application number	US-96824610-A
Country	US
Kind code	B2
Filing date	Dec 14, 2010
Priority date	Dec 14, 2010
Publication date	Feb 23, 2016
Grant date	Feb 23, 2016

Abstract

Methods and a computing device are disclosed. A computing device may aggregate a number of inputs indicative of a presence or an absence of a human being within a proximity of the computing device. A source of at least one of the inputs may be a human presence sensor. A source of other inputs may provide an indication of the presence of a human being with corresponding estimated probabilities or corresponding estimated reliabilities which may provide an estimate of an accuracy of respective indications. In some embodiments, if any of the number of inputs indicate the presence of a human being, the computing device may determine that a human being is present. In other embodiments, if a corresponding estimated probability or reliability of an input is less than a predetermined value, then the input may be discarded when determining whether a human being is present.

First claim

We claim as our invention:

1. A machine-implemented method of detecting a presence or an absence of a human being, the machine-implemented method comprising:
aggregating a plurality of inputs, at least one of the plurality of inputs being from a human presence sensor for detecting the presence or the absence of the human being within a given proximity of a computing device;
discarding a set of said plurality of inputs having a reliability less than a threshold value;
obtaining corresponding estimated probabilities of the presence of the human being from the undiscarded inputs that indicate the presence of the human being;
determining that the human being is present when any of the obtained estimated probabilities is greater than a predetermined value; and
causing a computing device to behave in a predetermined manner when the determining determines that the human being is absent, wherein
the machine-implemented method is performed by the computing device.

2. The machine-implemented method of claim 1 , wherein the human presence sensor provides an input indicating one of a group, said group comprising: present, not-present, and unknown.

3. The machine-implemented method of claim 1 , wherein: the human presence sensor performs reflective infrared proximity and presence detection.

4. The machine-implemented method of claim 3 , wherein
the corresponding estimated probability of the presence of the human being, with respect to the human presence sensor, is 100% when the input from the human presence sensor indicates that the human being is present.

5. The machine-implemented method of claim 1 , wherein:
at least a second one of the plurality of inputs is from a touch input device,
the corresponding estimated probability of the presence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the at least a second one of the plurality of inputs provides an input indicating that the human being is present.

6. The machine-implemented method of claim 1 , wherein
at least a second one of the plurality of inputs is from an orientation sensor, and
the corresponding estimated probability of the presence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the at least a second one of the plurality of inputs provides an input indicating a change in orientation.

7. The machine-implemented method of claim 1 , wherein
at least a second one of the plurality of inputs is provided by an application, and
the corresponding estimated probability of the presence or the absence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the application provides the at least a second one of the plurality of inputs.

8. A computing device comprising:
at least one processor; and
a memory connected to the at least one processor;
at least one item from a group consisting of a memory and a combination of the memory and at least one hardware logic component, the at least one item being configured to cause the computing device to perform a method comprising:
aggregating a plurality of inputs, at least one of the plurality of inputs being from a respective human presence sensor for detecting a presence or an absence of a human being within a given proximity of the computing device;
discarding a set said plurality of inputs having a reliability less than a threshold value;
determining whether the human being is present or absent, the determining determines that the human being is present when any of the undiscarded inputs indicates that the human being is present; and
causing the computing device to perform one or more actions when the human being is either determined to be present or is determined to be absent.

9. The computing device of claim 8 , wherein the respective human presence sensor provides an input indicating one from a group consisting of present, not present, and unknown.

10. The computing device of claim 8 , wherein the human presence sensor performs reflective infrared proximity and presence detection.

11. The computing device of claim 8 , wherein at least a second one of the inputs is from an application.

12. The computing device of claim 8 , wherein the at least some of the plurality of inputs are from devices including one or more devices from a group consisting of a touch input device and an orientation sensor.

13. A machine-implemented method of detecting a presence or an absence of a human being, the machine-implemented method comprising:
aggregating a plurality of inputs, at least one of the plurality of inputs being from a human presence sensor for detecting the presence or the absence of the human being within a given proximity of a computing device;
obtaining corresponding estimated probabilities of the presence of the human being with respect to ones of the plurality of inputs that indicate the presence of the human being;
determining that the human being is present when any of the obtained estimated probabilities is greater than a predetermined value, wherein the reliability of at least some of the plurality of inputs deteriorates over a predetermined time period after detection of the human being; and the determining whether the human being is present or absent further comprises discarding ones of the at least some of the plurality of inputs having a reliability less than a threshold value when performing the determining; and
causing a computing device to behave in a predetermined manner when the determining determines that the human being is absent, wherein
the machine-implemented method is performed by the computing device.

14. The machine-implemented method of claim 13 , wherein the human presence sensor provides an input indicating one of a group, said group comprising: present, not-present, and unknown.

15. The machine-implemented method of claim 13 , wherein: the human presence sensor performs reflective infrared proximity and presence detection.

16. The machine-implemented method of claim 15 , wherein
the corresponding estimated probability of the presence of the human being, with respect to the human presence sensor, is 100% when the input from the human presence sensor indicates that the human being is present.

17. The machine-implemented method of claim 13 , wherein:
at least a second one of the plurality of inputs is from a touch input device,
the corresponding estimated probability of the presence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the at least a second one of the plurality of inputs provides an input indicating that the human being is present.

18. The machine-implemented method of claim 13 , wherein
at least a second one of the plurality of inputs is from an orientation sensor, and
the corresponding estimated probability of the presence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the at least a second one of the plurality of inputs provides an input indicating a change in orientation.

19. The machine-implemented method of claim 13 , wherein
at least a second one of the plurality of inputs is provided by an application, and
the corresponding estimated probability of the presence or the absence of the human being, with respect to the at least a second one of the plurality of inputs, deteriorates over time after the application provides the at least a

Assignees

• Gear Gavin Michael
• Subramanian Nikhil
• Paulson Kevin Phillip
• Scott Jason
• Petrbok Milos
• Microsoft Technology Licensing Llc

Inventors

• Gear Gavin Michael
• Subramanian Nikhil
• Paulson Kevin Phillip
• Scott Jason
• Petrbok Milos

Classifications

• G06F1/3231 Primary

  Monitoring the presence, absence or movement of users · CPC title

• Y02B60/1289

  Cross-Sectional Technologies · mapped topic

• H04W76/14

  Direct-mode setup · CPC title

• Y02D10/00

  Energy efficient computing, e.g. low power processors, power management or thermal management · CPC title

• H04W4/80

  Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication · CPC title