Touch screen device facilitating estimation of entity orientation and identity
Devices, systems, computer-implemented methods, and computer program products that can facilitate estimating orientation and/or identity of an entity that touches a touch screen device are provided. According to an embodiment, a device can comprise a pixelated touch screen that provides a two-dimensional capacitance map in response to detection of one or more entities touching the pixelated touch screen. Capacitance data of the two-dimensional capacitance map is inversely proportional to a distance between fingers of the one or more entities and the pixelated touch screen. The device can further comprise a processor that applies an analytic method to the two-dimensional capacitance map to estimate orientation or identity of the one or more entities.
1. An input-output device, comprising:
a pixelated touch screen that generates a two-dimensional capacitance map in response to detection of one or more entities touching the pixelated touch screen, wherein capacitance data of the two-dimensional capacitance map is inversely proportional to a distance between fingers of the one or more entities and the pixelated touch screen; and
a processor that applies an analytic method to the two-dimensional capacitance map to determine whether an entity of the one or more entities is located in a back seat of a vehicle based on matching one or more capacitance data characteristics of the entity to a portion of the capacitance data.
2. The input-output device of claim 1 , wherein the analytic method comprises at least one of: a signal processing analysis; a principal component analysis; a first principles analysis; a machine learning model; or an imaging analysis.
3. The input-output device of claim 1 , wherein the analytic method uses machine learning over time to learn the one or more capacitance data characteristics of the entity.
4. The input-output device of claim 1 , wherein the processor determines an identity of the entity based on the analytic method.
5. The input-output device of claim 1 , wherein the one or more capacitance data characteristics is representative of one or more characteristics of the entity selected from a group consisting of: skin moisture level, width of a finger, and length of the finger.
6. The input-output device of claim 1 , further comprising:
an operation component that prohibits operation by the entity of an input control of a set of input controls of a user interface displayed on the pixelated touch screen based on a result of the determination of whether the entity is located in the back seat of the vehicle.
7. The input-output device of claim 1 , wherein the pixelated touch screen is selected from a group consisting of: a capacitance touch screen; a surface capacitance touch screen; a projected capacitance touch screen; a capacitance sensing touch-based input device; a capacitance sensing touch display; a capacitance sensing touch monitor; and a capacitance sensing touch pad.
8. The input-output device of claim 1 , wherein the two-dimensional capacitance map is selected from a group consisting of: a capacitance readout profile; a capacitance line plot; and a two-dimensional capacitance readout profile.
9. A computer-implemented method, comprising:
generating, by an input-output device operatively coupled to a processor, a two-dimensional capacitance map in response to detection of one or more entities touching a pixelated touch screen, wherein capacitance data of the two-dimensional capacitance map is inversely proportional to a distance between fingers of the one or more entities and the pixelated touch screen; and
applying, by the input-output device, an analytic method to the two-dimensional capacitance map to determine whether an entity of the one or more entities is located in a back seat of a vehicle based on matching one or more capacitance data characteristics of the entity to a portion of the capacitance data.
10. The computer-implemented method of claim 9 , wherein the analytic method comprises at least one of: a signal processing analysis; a principal component analysis; a first principles analysis; a machine learning model; or an imaging analysis.
11. The computer-implemented method of claim 9 , wherein the analytic method uses machine learning over time to learn the one or more capacitance data characteristics of the entity.
12. The computer-implemented method of claim 9 , further comprising determining, by the input-output device, an identity of the entity based on the analytic method.
13. The computer-implemented method of claim 9 , wherein the one or more capacitance data characteristics is representative of one or more characteristics of the entity selected from a group consisting of: skin moisture level, width of a finger, and length of the finger.
14. The computer-implemented method of claim 9 , further comprising:
prohibiting, by the input-output device, operation by the entity of an input control of a set of input controls of a user interface displayed on the pixelated touch screen based on a result of the determination of whether the entity is located in the back seat of the vehicle.
15. A computer program product facilitating an entity identification process, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
generate a two-dimensional capacitance map in response to detection of one or more entities touching a pixelated touch screen, wherein capacitance data of the two-dimensional capacitance map is inversely proportional to a distance between fingers of the one or more entities and the pixelated touch screen; and
apply an analytic method to the two-dimensional capacitance map to determine whether an entity of the one or more entities is located in a back seat of a vehicle based on matching one or more capacitance data characteristics of the entity to a portion of the capacitance data.
16. The computer program product of claim 15 , wherein the analytic method comprises at least one of: a signal processing analysis; a principal component analysis; a first principles analysis; a machine learning model; or an imaging analysis.
17. The computer program product of claim 15 , wherein the analytic method uses machine learning over time to learn the one or more capacitance data characteristics of the entity.
18. The computer program product of claim 15 , wherein the processor is further configured to determine an identity of the entity based on the analytic method.
19. The computer program product of claim 15 , wherein the one or more capacitance data characteristics is representative of one or more characteristics of the entity selected from a group consisting of: skin moisture level, width of a finger, and length of the finger.
20. The computer program product of claim 15 , wherein the processor is further configured to prohibit operation by the entity of an input control of a set of input controls of a user interface displayed on the pixelated touch screen based on a result of the determination of whether the entity is located in the back seat of the vehicle.