Physical device inspection or repair
In certain embodiments, device inspection or repair may be facilitated via signal-based determinations. In some embodiments, one or more flaws may be detected on a portion of a device via an optical sensor. Based on the detection, a physical structure may be caused to physically interact with the portion of the user device. Information indicating signals from the physical interaction may be obtained. Based on the signal information, a determination of whether a repair process should be performed on the device may be effectuated. The device may be assigned to be repaired via the repair process based on the determination indicating that the repair process should be performed on the device. In some embodiments, the signal information may be provided to a prediction model to determine whether the repair process should be performed on the device.
1. A system for facilitating scratch detection and buffing, the system comprising:
a computer system that comprises one or more processors programmed with computer program instructions that, when executed, cause the computer system to:
provide training information as input to a neural network to generate predictions related to whether scratch buffing should be performed on mobile devices, the training information indicating signals from interactions with scratches of the mobile devices;
provide buffing result information as reference feedback to the neural network to cause the neural network to assess the predictions against the buffing result information, the neural network updating one or more portions of the neural network based on the neural network's assessment of the predictions, the buffing result information relating to performance of scratch buffing on the mobile devices, the buffing result information indicating whether scratch buffing should be performed on the mobile devices;
subsequent to the updating of the neural network, detect, via an optical sensor, one or more scratches on a portion of a mobile device;
cause, based on the detection, a physical structure to physically interact with the portion of the mobile device that comprises the one or more scratches of the mobile device;
obtain information indicating signals from the physical interaction of the physical structure with the portion of the mobile device, at least some of the signals being from interaction of the physical structure with the one or more scratches of the mobile device;
provide the obtained signal information to the neural network to determine whether scratch buffing should be performed on the mobile device, the neural network being configured to provide, without reliance on explicit physical dimensions of the one or more scratches, an output indicating whether scratch buffing should be performed on the mobile device; and
initiate an automated buffing process on the mobile device based on the determination indicating that scratch buffing should be performed on the mobile device.
2. The system of claim 1 , wherein the computer system is caused to: obtain, from the neural network, an indication to perform scratch buffing on the mobile device, wherein initiating the automated buffing process comprises initiating the automated buffing process on the mobile device based on the indication from the neural network.
3. The system of claim 1 , wherein the computer system is caused to:
obtain, from the neural network, a prediction related to a result of performing scratch buffing on the mobile device,
wherein determining whether scratch buffing should be performed comprises determining, based on the prediction related to the result, whether scratch buffing should be performed on the mobile device.
4. A method comprising:
detecting one or more flaws on a portion of a user device;
causing, based on the detection, a physical structure to physically interact with the portion
of the user device that comprises the one or more flaws of the user device; obtaining, by one or more processors, information indicating signals from the physical interaction of the physical structure with the portion of the user device;
determining, by one or more processors, based on the signal information, whether a repair process should be performed on the user device;
assigning, by one or more processors, the user device to be repaired via the repair process based on the determination indicating that the repair process should be performed on the user device; and
causing, by one or more processors, performance of the repair process based on the assignment of the user device.
5. The method of claim 4 , wherein at least some of the signals are from interaction of the physical structure with the one or more flaws of the user device, and wherein the determination of whether buffing should be performed on the user device is based on the signals from the interaction of the physical structure with the one or more flaws of the user device.
6. The method of claim 4 , wherein the one or more flaws comprises one or more scratches, cracks, or dents.
7. The method of claim 4 , wherein the repair process comprises buffing of the user device to mitigate the one or more flaws.
8. The method of claim 4 , further comprising:
providing, by one or more processors, training information as input to a prediction model to generate predictions related to whether the repair process should be performed on user devices, the training information indicating signals from interaction with flaws of the user devices;
providing, by one or more processors, repair result information as reference feedback to the prediction model, the prediction model updating one or more portions of the prediction model based on the predictions and the repair result information, the repair result information relating to performance of the repair process on the user devices, the repair result information indicating whether the repair process should be performed on the user devices; and
subsequent to the updating of the prediction model, providing, by one or more processors, the signal information as input to the prediction model to determine whether the repair process should be performed on the user device.
9. The method of claim 8 , further comprising:
obtaining, by one or more processors, from the prediction model, an indication to perform the repair process on the user device,
wherein assigning the user device comprises assigning the user device to be repaired via the repair process based on the indication from the prediction model.
10. The method of claim 8 , further comprising:
obtaining, by one or more processors, from the prediction model, a prediction related to a result of performing the repair process on the user device,
wherein determining whether the repair process should be performed comprises determining, based on the prediction related to the result, whether the repair process should be performed on the user device.
11. A non-transitory computer-readable media comprising instructions that, when executed by one or more processors, cause operations comprising:
obtaining information indicating signals from physical interaction of a physical structure with at least a portion of a user device, the portion of the user device comprising one or more flaws of the user device;
determining, based on the signal information, whether a repair process should be performed on the user device;
assigning the user device to be repaired via the repair process based on the determination indicating that the repair process should be performed on the user device; and
causing performance of the repair process based on the assignment of the user device.
12. The non-transitory computer-readable media of claim 11 , the operations further comprising:
detecting the one or more flaws on the portion of the user device; and
causing, based on the detection, the physical interaction of the physical structure with the portion of the user device.
13. The non-transitory computer-readable media of claim 11 , wherein at least some of the signals are from interaction of the physical structure with the one or more flaws of the user device, and wherein the determination of whether the repair process should be performed on the user device is based on the signals from the interaction of the physical structure with the one or more flaws of the user device.
14. The non-transitory computer-readable media of claim 11 , wherein the one or more flaws comprises one or more scratches, cracks, or dents.
15. The non-transitory computer-readable media of claim 11 , wherein the repair process comprises buffing of the user device to mitigate the one or more flaws.
16. The non-transitory computer-readable media of claim 11 , the operations further comprising:
providing training information as input to a prediction model to generate predictions related to whether the repair process should be performed on user devices, the training information indicating signals from interaction with flaws of the user devices;
providing repair result information as reference feedback to the prediction model, the prediction model updating one or more portions of the prediction model based on the predictions and the repair result information, the repair result information relating to performance of the repair process on the user devices, the repair result information indicating whether the repair process should be performed on the user devices; and
subsequent to the updating of the prediction model, providing the signal information as input to the prediction model to determine whether the repair process should be performed on the user device.
17. The non-transitory computer-readable media of claim 16 , the operations further comprising:
obtaining, by one or more processors, from the prediction model, an indication to perform the repair process on the user device,
wherein assigning the user device comprises assigning the user device to be repaired via the repair process based on the indication from the prediction model.
18. The non-transitory computer-readable media of claim 16 , the operations further comprising:
obtaining, by one or more processors, from the prediction model, a prediction related to a result of performing the repair process on the user device,
wherein determining whether the repair process should be performed comprises determining, based on the prediction related to the result, whether the repair process should be performed on the user device.