Wearable Predictive Text Synchronization with External Devices
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Solution Overview
Problem
Portable electronic devices, such as smartwatches, face challenges in maintaining predictive text functionality due to the lack of synchronization with external devices, leading to inconvenient manual input of frequently used words and data, exacerbated by smaller displays and difficult manipulation.
Innovation Solution
An electronic device establishes a communicative connection with an external device to receive auto-complete text input information, store it for usage with a keyboard process, and display recommended words, leveraging AI self-learning on user data and user-defined text shortcuts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predictive text data is stored locally on wearable devices, then device independence is improved, but data synchronization with external devices is lost
Solution Approach 1:
The patent introduces a cloud server as an intermediary to synchronize predictive text data between external devices (smartphones) and wearable devices. The server receives user data from the external device, processes it, and transmits it back to the wearable device, enabling data synchronization without requiring direct connection between devices.
Solution Approach 2:
The system implements feedback mechanisms where the wearable device sends user input data to the external device via the cloud server, and the processed predictive text data is fed back to the wearable device. This continuous feedback loop ensures that predictive text functionality is maintained while data remains synchronized across devices.
2Reliability
If wearable devices store predictive text data independently, then device autonomy is improved, but user convenience deteriorates
Solution Approach 1:
The patent enables the wearable device to serve multiple functions by integrating predictive text capability that leverages data from external devices. The wearable device not only stores its own user data but also accesses and utilizes predictive text information from the external device, creating a multi-functional system that improves both reliability and ease of operation.
Solution Approach 2:
The system merges the predictive text data from the external device with the local data on the wearable device. By combining data sources through cloud synchronization, the system achieves more accurate predictive text functionality while maintaining device autonomy, thereby improving user convenience.
3Adaptability or versatility
If predictive text is synchronized across devices, then user experience consistency is improved, but data transmission complexity increases
Solution Approach 1:
The cloud server acts as a mediator that simplifies the synchronization process between devices. Instead of implementing complex direct peer-to-peer synchronization protocols, the system uses the cloud server to handle data transmission, processing, and routing, thereby reducing the complexity of cross-device data synchronization.
Solution Approach 2:
The synchronization system is segmented into distinct components: the external device, the cloud server, and the wearable device. Each component has a specific function in the data transmission process, which modularizes the complexity and makes the overall system easier to implement and maintain while achieving cross-device compatibility.
Data Source
AI summary
An electronic device and method are disclosed. The electronic device includes communication circuitry, a display, memory and a processor. The processor implements the method, including: establishing, by control of the processor, a communicative connection to an external device via the communication circuitry; receiving via the communicative connection, auto-complete text input information from the external device; storing, in the memory, the received auto-complete text input information, for usage with a keyboard process of the electronic device; and displaying, via a display, a recommended word, based on the stored auto-complete text input information, wherein the auto-complete text input information includes at least one of user data including complete words for recommendation as predictive text, generated from collecting and applying artificial-intelligence (AI) self-learning on words frequently utilized by a user, and user-defined text shortcuts configured by the user which associate an incomplete input with a completed word for usage as the predictive text.