Autonomous Ringer Profile Switcher for Mobile Devices
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Solution Overview
Problem
Users of computing devices such as smartphones and smartwatches often forget to mute or unmute the ringer during important events, leading to either unwanted disturbances or missed notifications due to manual errors in managing ringer settings.
Innovation Solution
Implementing a system that uses machine learning models to create decision rules based on sensor data and user behavior to automatically switch between ringer settings, such as muting or unmuting the device based on predefined rules related to location and scheduled events, allowing for seamless management of ringer profiles without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual ringer control is used, then user autonomy is maintained, but human error increases leading to inappropriate ringer states
Solution Approach 1:
The system automatically monitors sensor data (location, calendar events) and autonomously adjusts ringer settings without requiring user intervention. The device serves itself by detecting contextual cues and applying decision rules to mute or unmute the ringer appropriately, eliminating manual operation while maintaining reliability.
Solution Approach 2:
The system continuously monitors sensor data and calendar events as feedback inputs, processes this information through decision rules, and automatically adjusts ringer settings in response. This closed-loop feedback mechanism ensures the ringer state consistently matches the detected context, improving reliability without manual input.
2Reliability
If automatic ringer control based on sensor data and decision rules is implemented, then human error is reduced, but system complexity increases
Solution Approach 1:
The automation system is segmented into distinct functional modules: sensor data acquisition, calendar event retrieval, decision rule evaluation, and ringer control execution. Each module handles a specific aspect of the automation process, making the overall complex system manageable and maintainable through clear separation of concerns.
3Reliability
If continuous monitoring of sensor data and calendar events is performed, then ringer settings are continuously optimized, but energy consumption increases
Solution Approach 1:
The system performs periodic monitoring of sensor data and calendar events at appropriate intervals rather than continuous monitoring. This periodic action maintains reliable ringer setting optimization while significantly reducing energy consumption compared to continuous monitoring, as the device only activates sensors and processing when needed based on contextual changes.
Data Source
AI summary
In some examples, a computing device may receive sensor data from a plurality of sensors and determine a location of the computing device in three-dimensions. A calendar application executing on the computing device may be accessed to determine that a first event is currently scheduled. A setting may indicate that a ringer of the computing device is unmuted to enable the ringer to be heard when the computing device receives an incoming communication (e.g., a call, a text, or a message). If the sensor data, the first event, or both satisfy a particular rule of a set of decision rules, the computing device may automatically modify the setting to mute the ringer based on the particular rule. If a user of the computing device modifies the setting to unmute the ringer, the computing device may send modification data associated with the modification to a server.