CONTEXT-BASED SMARTPHONE SENSOR LOGIC
Methods employ sensors in portable devices (e.g., smartphones) both to sense content information (e.g., audio and imagery) and context information. Device processing is desirably dependent on both. For example, some embodiments activate certain processor intensive operations (e.g., content recognition) based on classification of sensed content and context. The context can control the location where information produced from such operations is stored, or control an alert signal indicating, e.g., that sensed speech is being transcribed. Some arrangements post sensor data collected by one device to a cloud repository, for access and processing by other devices. Multiple devices can collaborate in collecting and processing data, to exploit advantages each may have (e.g., in location, processing ability, social network resources, etc.). A great many other features and arrangements are also detailed.
1 - 9 . (canceled)
10 . A method performed by a hardware system configured by software instructions, the method comprising the acts:
receiving first audio and/or visual information, and applying a classification procedure to said received first information to identify its type;
determining a first scenario type, based at least in part on one or more of time of day, day of week, location, calendar data, clock alarm status, motion sensor data, orientation sensor data, and information from a social networking service;
based on the identified type of the received first information, and based on the determined first scenario type, applying a first group of one or more recognition technologies to the received first information;
receiving second audio and/or visual information, and applying a classification procedure to said received second information to identify its type;
determining a second scenario type, based at least in part on one or more of time of day, day of week, location, calendar data, clock alarm status, motion sensor data, orientation sensor data, and information from a social networking service;
based on the identified type of the received second information, and based on the determined second scenario type, applying a second group of one or more recognition technologies to the received second information;
receiving third audio and/or visual information, and applying a classification procedure to said received third information to identify its type;
determining a third scenario type, based at least in part on one or more of time of day, day of week, location, calendar data, clock alarm status, motion sensor data, orientation sensor data, and information from a social networking service; and
based on the identified type of the received third information, and based on the determined third scenario type, applying a third group of one or more recognition technologies to the received third information;
wherein the first, second and third groups of applied recognition technologies are different, and at least one of said groups of applied recognition technologies includes two or more recognition technologies.
11 - 57 . (canceled)
58 . The method of claim 10 in which the received first, second and third audio and/or visual information all comprises audio information.
59 . The method of claim 10 in which the received first, second and third audio and/or visual information all comprises visual information.
60 . The method of claim 10 in which at least one of said first, second and third scenario types is based on time of day.
61 . The method of claim 10 in which at least one of said first, second and third scenario types is based on day of week.
62 . The method of claim 10 in which at least one of said first, second and third scenario types is based on location.
63 . The method of claim 10 in which at least one of said first, second and third scenario types is based on calendar data.
64 . The method of claim 10 in which at least one of said first, second and third scenario types is based on clock alarm status.
65 . The method of claim 10 in which at least one of said first, second and third scenario types is based on motion sensor data.
66 . The method of claim 10 in which at least one of said first, second and third scenario types is based on orientation sensor data.
67 . The method of claim 10 in which at least one of said first, second and third scenario types is based on information from a social networking service.
68 . The method of claim 10 in which one of said first, second and third groups of recognition technologies includes watermark decoding technology, and another of said first, second and third groups of recognition technologies does not include watermark decoding technology.
69 . The method of claim 10 in which one of said first, second and third groups of recognition technologies includes fingerprinting technology, and another of said first, second and third groups of recognition technologies does not include fingerprinting technology.
70 . The method of claim 10 in which one of said first, second and third groups of recognition technologies includes barcode decoding technology, and another of said first, second and third groups of recognition technologies does not include barcode decoding technology.
71 . The method of claim 10 in which one of said first, second and third groups of recognition technologies includes optical character recognition technology, and another of said first, second and third groups of recognition technologies does not include optical character recognition technology.
72 . The method of claim 10 that further includes:
receiving fourth audio and/or visual information, and applying a classification procedure to said received fourth information to identify its type;
determining a fourth scenario type, based at least in part on one or more of time of day, day of week, location, calendar data, clock alarm status, motion sensor data, orientation sensor data, and information from a social networking service; and
based on the identified type of the received fourth information, and based on the determined fourth scenario type, applying a fourth group of one or more recognition technologies to the received fourth information;
wherein the first, second, third and fourth groups of applied recognition technologies are different; two of said received first, second, third or fourth audio and/or visual information comprise audio information; and two of said received first, second, third or fourth audio and/or visual information comprise visual information.
73 . A method performed by a user's battery-powered portable device, configured by software instructions, the method comprising the acts:
receiving first visual information;
determining a first scenario type, based at least in part on one or more of context factors from the list consisting of: time of day, day of week, location, user calendar data, user clock alarm status, motion sensor data, orientation sensor data, and information from a social networking service;
identifying a first recognition agent based at least in part on the first scenario type, and launching the identified first recognition agent to process the first visual information;
receiving second visual information;
determining a second scenario type, based at least in part on one or more of context factors from said list; and
identifying a second recognition agent based at least in part on the second scenario type, and launching the identified second recognition agent to process the second visual information;
wherein the first and second visual information are different, the first and second scenario types are different, and the first and second recognition agents are different, wherein the device seems to respond intuitively by activating different recognition agents based on different device contexts.
74 . The method of claim 73 that includes capturing the first and second visual information using a camera of said battery-powered portable device.
75 . The method of claim 73 that further includes applying a classification procedure to the received first visual information to identify its type, and identifying the first recognition agent based on both the identified type of the received first information, and on said first scenario type.