Notification Management via Activity Sensor Feedback
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Solution Overview
Problem
Current smartphones lack the ability to dynamically adjust alarm and notification settings based on user activity levels and transitions, which can lead to unnecessary disturbances or missed reminders.
Innovation Solution
A processor-based personal electronic device that uses data from onboard and remote sensors, such as motion, location, and ambient light sensors, along with calendar entries, to infer user activity and automatically adjust notifications, reminders, and device settings, such as generating reminders to stand up and stretch after sedentary periods or starting specific music playlists during exercise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If notifications are continuously delivered to keep user informed, then information delivery is improved, but user distraction and disturbance increase
Solution Approach 1:
The notification system dynamically adjusts its behavior based on real-time activity level detection. When low activity is detected, notifications are delivered normally. When high activity is detected, notifications are suppressed or delayed. This dynamic adaptation resolves the contradiction by making notification delivery conditional on current user state rather than static.
Solution Approach 2:
The system uses sensors to continuously monitor activity levels and feeds this information back to the notification controller. This feedback loop enables the system to automatically adjust notification delivery based on detected user activity, resolving the contradiction between keeping user informed and avoiding distraction.
2Object-affected harmful factors
If Do Not Disturb mode is manually activated to reduce distractions, then user disturbance is reduced, but user convenience and responsiveness decrease
Solution Approach 1:
The system automatically detects activity levels and autonomously activates or deactivates Do Not Disturb mode without requiring manual user intervention. The sensors monitor user state and the system self-adjusts notification behavior accordingly, eliminating the need for users to manually manage DND settings while maintaining convenience.
Solution Approach 2:
The system proactively detects changes in activity levels and preemptively adjusts notification delivery before the user would need to manually intervene. By monitoring sensors continuously, the system prepares and executes notification suppression in advance based on detected activity patterns.
3Loss of information
If activity monitoring is continuously performed to enable dynamic notification adjustment, then notification relevance is improved, but device energy consumption increases
Solution Approach 1:
The system performs partial monitoring by focusing on key activity indicators that are most relevant to notification delivery decisions. Rather than continuously analyzing all sensor data at full resolution, the system monitors for significant activity level changes that would trigger notification behavior changes, reducing energy consumption while maintaining effectiveness.
Data Source
AI summary
A processor-based personal electronic device (such as a smartphone) is programmed to automatically respond to data sent by various sensors from which the user's activity may be inferred. One or more of the sensors may be worn by the user and remote from the device. A wireless communication link may be used by the device to obtain remote sensor data. Data from on-board sensors in the device—such as motion sensors, location sensors, and the like—may also be used to deduce the user's current activity. In one embodiment, an extended period of inactivity triggers a reminder to the user to get up, stretch and move about. In other embodiments, transitions in a user's activity level may be used to trigger reminders and/or set the state of the device (such as a Do Not Disturb state wherein notifications and alarms are suppressed).