A computing device and method for cloud-assisted perceptual computing is described. The computing device includes a sensor to collect data for perceptual computing. The computing device also includes an analytics determiner to calculate a disposition result based on the data collected by the sensor and to calculate a confidence level of the disposition result. The computing device compares the confidence level to a threshold and sends the data to a cloud computing device in response to the confidence level being below the threshold.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computing device comprising: a sensor to collect data for perceptual computing; an analytics determiner to: calculate a disposition result based on the data collected by the sensor; and calculate a confidence level of the disposition result; and a comparison manager to: compare the confidence level to a threshold; and send the data to a cloud computing device in response to the confidence level being below the threshold. 2. The computing device of claim 1, comprising a processor, wherein the computing device comprises an Internet-of-Things (IoT) device, wherein the analytics determiner comprises code stored in memory of the computing device and executable by the processor, and wherein the computing device comprises a client computing device external to a cloud comprising the cloud computing device. 3. The computing device of claim 1, comprising a processor, wherein the computing device comprises a client computing device comprising an IoT network server, an IoT gateway device, or an IoT smart sensor, wherein the comparison manager comprises code stored in memory of the computing device and executable by the processor, wherein the client computing device to communicate with the cloud computing device via a network comprising a local area network or a wide area network, or both. 4. The computing device of claim 1, wherein the computing device comprises an IoT edge device or a node to communicate with other sensors not comprising the first sensor, and wherein the threshold comprises a numerical value specified by a user. 5. The computing device of claim 1, wherein the confidence level is a function of multiple confidence levels assigned by the computing device respectively to analytics subject categories. 6. The computing device of claim 5, wherein the function is a weighted average of a user-defined subset of the multiple confidence levels assigned by the computing device respectively to the analytics subject categories. 7. The computing device of claim 1, wherein the computing device to initiate an action by the computing device in response to the confidence level being above the threshold. 8. The computing device of claim 1, wherein to calculate a disposition result comprises determining a prediction result for an analytics subject category for the data collected by the sensor. 9. The computing device of claim 8, wherein the confidence level comprises a probability that the prediction result for the analytics subject category matches a pre-dispositioned result for the analytics subject category. 10. A computing device comprising: a sensor to collect data for perceptual computing; a first processor; and a first memory storing a first code executable by the first processor to: calculate a first disposition result based on the data collected by the sensor; calculate a first confidence level of the first disposition result; compare the first confidence level to a first threshold; and send the data to a cloud computing device in response to the first confidence level being below the first threshold. 11. The computing device of claim 10, wherein the computing device comprises a client computing device comprising an IoT edge device. 12. The computing device of claim 10, wherein the first threshold comprises a numerical value specified by a user, and wherein the first confidence level is a function of multiple confidence levels assigned by the computing device respectively to analytics subject categories. 13. The computing device of claim 12, wherein the function is a weighted average of a user-defined subset of the multiple confidence levels assigned by the computing device respectively to the analytics subject categories. 14. The computing device of claim 10, wherein the first memory stores code executable by the first processor to initiate an action by the computing device in response to the first confidence level being above the first threshold. 15. The computing device of claim 10, wherein the cloud computing device comprises: a second processor; and a second memory storing a second code executable by the second processor to: calculate a second disposition result based on the data received from the computing device; calculate a second confidence level of the second disposition result; compare the second confidence level to a second threshold; and initiate an action by the computing device in response to the second confidence level being above the second threshold. 16. The computing device of claim 10, wherein the computing device comprises an Internet of Things (IoT) device, the IoT device comprising a gateway, an edge device, or an aggregation device. 17. A method by a computing device, comprising: calculating a disposition result based on data collected by a sensor; calculating a confidence level of the disposition result; comparing the confidence level to a threshold; and sending the data to a cloud computing device in response to the confidence level being below the threshold. 18. The method of claim 17, wherein the computing device is a client computing device comprising an IoT edge device. 19. The method of claim 17, comprising receiving a value of the threshold from a user, wherein the confidence level is a function of multiple confidence levels calculated and assigned respectively by the computing device to analytics subject categories. 20. The method of claim 19, wherein the function comprises a weighted average of a user-defined subset of the multiple confidence levels assigned respectively by the computing device to the analytics subject categories. 21. The method of claim 17, comprising initiating an action by the computing device in response to the confidence level being above the threshold. 22. The method of claim 17, comprising communicating with the cloud computing device via a network, wherein the network comprises a local area network or a wide area network, or both. 23. At least one computer-readable medium, comprising instructions to direct a processor to: calculate a disposition result based on data collected by a sensor; calculate a confidence level of the disposition result; compare the confidence level to a threshold; and send the data to a cloud computing device in response to the confidence level being below the threshold. 24. The at least one computer-readable medium of claim 23, comprising instructions to direct the processor to receive a value of the threshold from a user. 25. The at least one computer-readable medium of claim 23, comprising instructions to direct the processor to initiate an action in response to the confidence level being above the threshold.