BACKGROUND

The present invention relates generally to the field of resolving user-interface functionality, and more particularly to offloading a failed user-interface functionality to a proximate mobile device.

Fast-food restaurants have evolved from traditionally receiving customer orders over the counter via human interaction to receiving customer orders electronically via Internet-enabled computing devices. As a customer enters a restaurant, that customer may simply approach a self-order kiosk, choose items from a menu, provide payment information, and receive an order confirmation. Placing an order for food or drinks has been simply transferred from interacting with a restaurant employee to a self-service kiosk, replacing human interaction with technology interaction.

Many more mobile device user-interface displays are switching to touch screen displays for the self-serve kiosks as part of the emergence of Internet of Things (IoT) capabilities. IoT refers to the concept of extending internet connectivity beyond conventional computing platforms such as personal computers and mobile devices, and into any range of traditionally non-internet-enabled physical devices and everyday objects. Embedded with electronics, internet connectivity, and other forms of hardware (such as sensors), these devices and objects can communicate and interact with customers over a network connection, and the devices and objects can be remotely monitored and controlled.

SUMMARY

Aspects of the present invention disclose a method, computer program product, and computer system for resolving failed user-interface functionality. One embodiment of the invention may include a local device having one or more processors configured to detect, at one or more user-selectable elements displayed on a local device user-interface, a first user input having a first input magnitude. Further, one or more processors may be configured to determine that the local device user-interface is not responsive to the first user input. The local device one or more processors may also be configured to detect, at the one or more user-selectable elements, a second user input by the user, the second user input having a second input magnitude that is greater than the first input magnitude.

Further, the local device one or more processors may be configured to determine that the local device user-interface is not responsive to the second user input. The one or more processors may be configured to determine non-responsiveness by detecting user aggravation as multiple repeated screen touches, user audible frustration through a microphone, or user cancellation of the interaction by touching a cancel user-selectable element on the local device user-interface. If the local device one or more processors determines the local device user-interface is not responsive, then the local device one or more processors may transmit first data to a mobile device associated with the user, the first data corresponding to a user-interface offload prompt, wherein the mobile device may be within a predetermined proximity of the local device user-interface. Furthermore, the local device one or more processors may be configured to receive second data from the mobile device, the second data may correspond to a plurality of mobile device user inputs received at the mobile device.

In another embodiment, the one or more processors may be configured to determine that the local device user-interface is not responsive to the first user input because the one or more processors failed to execute a command corresponding to the one or more user-selectable elements initiated by the first user input. Further, the mobile device may include one or more processors that may be configured to perform embodiments of the invention described herein. For example, an embodiment of the invention may include one or more processors of a mobile device configured to generate a mobile device user-interface on a display of the mobile device, wherein the mobile device user-interface may include mobile device user-selectable elements corresponding to the one or more user selectable elements.

The user-interface offload prompt may be transmitted to the mobile device in response to determining that the local device user-interface is not responsive to the second user input. At least one of the plurality of mobile device user inputs may correspond to the first user input at the one or more user-selectable elements. The mobile device one or more processors may be configured to transmit the second data to a local device comprising the local device user interface, wherein the local device is connected to a network. The local device may include a wireless communication module configured to facilitate wireless communications between the local device and the mobile device when within the predetermined proximity of the local device.

In another embodiment, the local device one or more processors may be configured for monitoring user interaction. User interaction may be monitored by receiving data from sensors configured to detect user movement, user inputs, or user activity. Further, the one or more sensors may be configured for tracking metrics received from monitoring user interactions. Examples of metrics that may be tracked are sensor data (e.g., pressure, input, audio) or some indication of input cancellation.

In an embodiment, the local device one or more processors may be configured for processing and analyzing the metrics or metric data to determine if the metrics bear any correlation to user aggravation. If the analysis produces results indicating user aggravation, then the local device one or more processors may be configured to offload the local device user interface functionality to a proximate mobile device for display and user interaction on the mobile device user-interface. In other words, the mobile device one or more processors may be configured to mirror the functionality of the local device user-interface on the mobile device user-interface via a wireless data transmission from the local device to the mobile device. However, if the analysis produces results that do not point to user aggravation, the local device one or more processors may be configured to continuously process and analyze the metrics or metric data.

