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Adjusting Mobile Device State Based on User Intentions And/or Identity
| Content Provider | The Lens |
|---|---|
| Abstract | In one embodiment, a method includes receiving data associated with multiple first client devices, the data corresponding to a first set of sensor values and physical-state indicators of the first client devices; receiving data associated with a second client device corresponding to a second set of sensor values, the second client device including a first and a second set of sensors; generating functions that each determine a probability that the second client device is in a particular physical state, wherein the determination includes correlating the second set of sensor values with a corresponding physical state of the second client device based on the data associated with the multiple first client devices, and wherein a first function is based on values of the first set of sensors and a second function is based on values of the second set of sensors; and sending the generated functions to the second client device. |
| Related Links | https://www.lens.org/lens/patent/013-457-086-601-941/frontpage |
| Language | English |
| Publisher Date | 2017-03-02 |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Patent |
| Jurisdiction | United States of America |
| Date Applied | 2016-11-09 |
| Applicant | Facebook Inc |
| Application No. | 201615347199 |
| Claim | A method comprising: by a computing device, receiving data associated with a plurality of first client devices, the data associated with each of the first client devices corresponding to a first set of sensor values and one or more indicators that each correspond to one of a plurality of physical states of the each of the first client devices; by the computing device, receiving data associated with a second client device corresponding to a second set of sensor values, the second client device comprising a first and a second set of sensors; by the computing device, generating a plurality of functions that each determine a probability that the second client device is in a respective one of the physical states, wherein the determination comprises correlating the second set of sensor values with a corresponding physical state of the second client device based on the data associated with the plurality of first client devices, and wherein a first function of the plurality of functions is based on sensor values of the first set of sensors and a second function of the plurality of functions is based on sensor values of the second set of sensors; and by the computing device, sending the plurality of functions to the second client device. The method of claim 1 , further comprising segregating the data based on a sensor type. The method of claim 1 , further comprising: representing the sensor values as a vector; and arranging the data in a data structure. The method of claim 3 , wherein the first function comprises a plurality of weights that are multiplied to each value of the vector. The method of claim 1 , wherein the plurality of functions are generated at predetermined intervals. The method of claim 1 , wherein the first function comprises one or more logical operators. The method of claim 1 , wherein the second function is computationally more complex than the first function. The method of claim 1 , wherein the first function is configured to output a value for each physical state of the second client device. The method of claim 1 , wherein the second function is configured to adjust the probability the second client device is in one of the particular physical states based on a time of day. The method of claim 1 , wherein the first set of sensor values comprises training data for a neural network. The method of claim 10 , wherein the neural network generates first or second function using backpropagation training. The method of claim 10 , wherein the neural network comprises a Hopfield, Elman, Jordan, Echo state, long short-term memory, bidirectional, or continuous time recurrent neural network. The method of claim 10 , wherein the neural network comprises one or more adaptive linear elements. The method of claim 1 , wherein the first set of sensors comprise low-power sensors. The method of claim 14 , wherein the first set of sensors are one or more capacitive touch sensors. The method of claim 1 , wherein the second set of sensors comprise sensors that are inactive in a locked or sleep mode of the second client device. The method of claim 16 , wherein the second set of sensors are an accelerometer, gyrometer, proximity sensor, or light sensor. The method of claim 1 , wherein the plurality of physical states each correspond to a particular use of a respective first or second client device. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive data associated with a plurality of first client devices, the data associated with each of the first client devices corresponding to a first set of sensor values and one or more indicators that each correspond to one of a plurality of physical states of the each of the first client devices; receive data associated with a second client device corresponding to a second set of sensor values, the second client device comprising a first and a second set of sensors; generate a plurality of functions that each determine a probability that the second client device is in a respective one of the physical states, wherein the determination comprises correlating the second set of sensor values with a corresponding physical state of the second client device based on the data associated with the plurality of first client devices, and wherein a first function of the plurality of functions is based on sensor values of the first set of sensors and a second function of the plurality of functions is based on sensor values of the second set of sensors; and send the plurality of functions to the second client device. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: receive data associated with a plurality of first client devices, the data associated with each of the first client devices corresponding to a first set of sensor values and one or more indicators that each correspond to one of a plurality of physical states of the each of the first client devices; receive data associated with a second client device corresponding to a second set of sensor values, the second client device comprising a first and a second set of sensors; generate a plurality of functions that each determine a probability that the second client device is in a respective one of the physical states, wherein the determination comprises correlating the second set of sensor values with a corresponding physical state of the second client device based on the data associated with the plurality of first client devices, and wherein a first function of the plurality of functions is based on sensor values of the first set of sensors and a second function of the plurality of functions is based on sensor values of the second set of sensors; and send the plurality of functions to the second client device. |
| CPC Classification | SELECTING WIRELESS COMMUNICATION NETWORKS Climate Change Mitigation Technologies In Information And Communication Technologies [Ict]; I.E. Information And Communication Technologies Aiming At The Reduction Of Their Own Energy Use COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ELECTRIC DIGITAL DATA PROCESSING Measuring Linear Or Angular Speed; Acceleration; Deceleration; Or Shock;Indicating Presence; Absence; Or Direction; Of Movement |
| Extended Family | 153-217-648-282-502 020-168-449-645-074 180-078-403-235-662 107-209-409-312-665 150-210-562-860-761 108-476-925-960-063 040-247-257-336-702 083-741-800-194-333 013-457-086-601-941 062-268-524-835-137 199-423-467-807-927 082-932-102-738-247 127-021-663-139-846 131-240-690-192-129 171-479-798-715-759 191-175-927-682-029 035-112-617-422-606 188-871-846-118-283 113-094-653-253-548 174-882-393-172-871 047-751-496-429-17X 001-174-468-495-843 133-287-757-369-226 142-989-261-528-177 120-164-428-622-196 188-516-143-422-557 105-274-241-090-648 087-802-449-324-007 144-364-622-336-609 151-210-064-936-491 028-447-102-782-208 140-914-808-089-974 045-370-016-229-493 097-906-366-546-682 033-743-663-203-349 018-415-667-772-411 143-686-219-275-688 011-971-106-055-028 096-012-127-814-61X |
| Patent ID | 20170064624 |
| Inventor/Author | Schillings Benoit M Garcia David Harry |
| IPC | H04W52/02 G06N3/04 G06N3/08 G06N7/00 |
| Status | Active |
| Owner | Meta Platforms Inc |
| Simple Family | 153-217-648-282-502 020-168-449-645-074 096-012-127-814-61X 180-078-403-235-662 150-210-562-860-761 040-247-257-336-702 108-476-925-960-063 083-741-800-194-333 013-457-086-601-941 062-268-524-835-137 082-932-102-738-247 199-423-467-807-927 127-021-663-139-846 131-240-690-192-129 171-479-798-715-759 191-175-927-682-029 188-871-846-118-283 035-112-617-422-606 113-094-653-253-548 047-751-496-429-17X 001-174-468-495-843 133-287-757-369-226 142-989-261-528-177 120-164-428-622-196 188-516-143-422-557 105-274-241-090-648 087-802-449-324-007 144-364-622-336-609 151-210-064-936-491 028-447-102-782-208 140-914-808-089-974 045-370-016-229-493 097-906-366-546-682 033-743-663-203-349 018-415-667-772-411 143-686-219-275-688 011-971-106-055-028 |
| CPC (with Group) | H04Q9/00 H04Q2209/10 H04Q2209/47 H04Q2209/43 H04Q2209/50 H04Q2209/823 H04W52/0212 H04W52/0254 Y02D30/70 G06N3/045 G06F1/3203 G06N3/08 G06N3/084 H04W8/22 G06N3/044 G06N7/01 G06F3/041 G01P15/18 |
| Issuing Authority | United States Patent and Trademark Office (USPTO) |
| Kind | Patent Application Publication |
