Notification Engine Proximity Filtering
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Solution Overview
Problem
Current reminder systems do not provide notifications effectively for entities or activities that are only available when open or within a user's proximity, failing to utilize user interest lists and location-based data to offer relevant and timely recommendations.
Innovation Solution
A notification system that determines whether an entity is open and within a predetermined distance from a user's device, providing notifications based on user interest lists and location data, offering recommendations for entities with similar topics and activities when the user is nearby.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system provides notifications for all entities in the user's interest list, then the user receives comprehensive information about entities they are interested in, but the user receives irrelevant notifications when entities are closed or outside proximity
Solution Approach 1:
The system performs preliminary checks before sending notifications by verifying entity status (open/closed) and user proximity to the entity location. This preliminary validation ensures that only relevant notifications are sent to users, filtering out irrelevant ones in advance and preventing waste of user time.
Solution Approach 2:
The system continuously monitors entity status changes and user location data, using this feedback to dynamically determine when to send notifications. By incorporating real-time feedback about entity availability and user proximity, the system ensures notifications are sent only when appropriate, improving relevance while reducing unnecessary communications.
2Speed
If the system continuously monitors entity status and user location to provide timely notifications, then notification timeliness is improved, but system complexity and resource consumption increase
Solution Approach 1:
The system leverages existing data sources and user device capabilities (location services, entity status APIs) to perform monitoring without requiring complex custom infrastructure. By utilizing self-service data collection from established sources, the system achieves timely notification delivery while minimizing added complexity.
Solution Approach 2:
The system uses a multi-functional architecture where a single notification engine handles diverse entity types (restaurants, events, appointments) and multiple notification channels. This universal approach consolidates complexity into a single system that can serve multiple purposes, reducing overall system complexity while maintaining timely notification capabilities.
3Reliability
If the system sends notifications only when entities are open and user is nearby, then notification relevance is improved, but the frequency of notifications decreases
Solution Approach 1:
The system dynamically adjusts notification parameters (proximity distance, time windows) based on entity type and user preferences. By changing these parameters adaptively, the system maintains high notification usefulness while optimizing frequency to balance relevance with adequate information flow to the user.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing recommendations to users. One of the methods includes receiving data indicating a selection, by a user, of a notification option relating to a first entity, adding the first entity to an interest list for the user, determining, based at least on adding the first entity to the interest list for the user, to provide a notification relating to an entity, and providing, based on determining to provide the notification relating to the entity, the notification.