Micro-location Notification Muting via Motion Prediction
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Solution Overview
Problem
Existing micro-location notification systems often send unwanted messages to users as they move through defined areas, leading to annoyance and inefficiency, as notifications are delivered after the user has left the relevant zone, causing recipients to ignore future marketing communications.
Innovation Solution
A computerized method that determines dwell time within a micro-location area and predicts the user's likelihood of remaining within the area during a relevancy period based on speed and direction of motion, muting messages if the user is likely to exit before processing the notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If notifications are sent to users when they enter micro-location areas, then marketing reach and user engagement are improved, but users receive unwanted messages when they are merely passing through, leading to annoyance and message fatigue
Solution Approach 1:
The system performs preliminary analysis of user motion characteristics (speed, direction, trajectory) before sending notifications. By predicting whether the user will remain in the micro-location area during the relevancy period based on their current motion state, the system prevents notification fatigue by only sending messages to users who are likely to stay, thus maintaining marketing effectiveness while reducing unwanted messages
Solution Approach 2:
The system continuously monitors user motion parameters (speed, direction, location changes) and uses this feedback to dynamically determine notification eligibility. The feedback loop compares predicted user location at the end of the relevancy period against the micro-location area boundaries, adjusting notification delivery decisions based on real-time motion analysis
2Device complexity
If notifications are sent based on simple presence detection, then implementation complexity is reduced, but notification timing becomes inaccurate as messages are delivered after users have left the relevant zone
Solution Approach 1:
The system calculates predicted user location and dwell time in advance before the relevancy period expires. By using current speed and direction to project future position, the system determines notification eligibility proactively, ensuring messages are sent at the optimal moment when users are still within or about to enter the micro-location area, eliminating delays while avoiding overly complex real-time tracking
Solution Approach 2:
The system dynamically adjusts notification timing based on user motion characteristics. By incorporating speed and direction variables into the dwell time calculation, the system adapts to different user behaviors (walking vs. standing, entering vs. exiting), optimizing notification delivery timing for each user's specific motion pattern without requiring complex adaptive algorithms
3Reliability
If the system monitors user motion parameters to improve notification accuracy, then notification relevance is improved, but computational requirements and processing time increase
Solution Approach 1:
The system applies partial monitoring by focusing only on the most critical motion parameters (speed, direction, location changes) needed for prediction, rather than comprehensive motion analysis. This selective approach achieves sufficient prediction accuracy for notification decisions while minimizing computational overhead and power consumption
Solution Approach 2:
The system uses the device's existing motion sensing capabilities (accelerometer, GPS, compass) that are already active for other purposes, eliminating the need for additional specialized sensors or high-power processing hardware. The notification prediction leverages data the device is already collecting for navigation and fitness tracking
Data Source
AI summary
In response to determining a physical presence of a person within a geographic micro-location area defined by virtual micro-location area boundaries, a computer processor determines a dwell time as an elapsed time that the person dwells within the micro-location area after determining the physical presence of the person. In response to the dwell time meeting a message trigger threshold, the computer processor determines whether the person is likely to be within the micro-location area at the end of a relevancy time period as a function of current geographic location position of the person, speed and direction of motion of the person, and distance to the micro-location area boundaries. If unlikely that the person will be within the micro-location area at the end of the relevancy time period, the processor mutes transmission to the person of a message associated with dwelling within the micro-location area for the trigger time.