Purchase Reminder System with Category-Based Timing
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Solution Overview
Problem
Existing car navigation systems fail to remind users of purchases in an appropriate and efficient manner, leading to unnecessary reminders and user effort in stopping these reminders.
Innovation Solution
An information processing method and system that obtains article information based on user preferences and outputs reminders when specific conditions are met, such as proximity to a store and a set reminding period, reducing user effort and minimizing unnecessary reminders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system continuously reminds the user of article purchase, then the user is ensured to remember the purchase, but the user experiences unnecessary reminders and increased operation effort to stop them
Solution Approach 1:
The system automatically detects when the user has purchased the article by monitoring sensor data (such as entering a store, making a purchase transaction, or returning home with the item) and autonomously stops the reminder notifications without requiring any manual intervention from the user. This self-service mechanism resolves the contradiction by maintaining reliable reminders while eliminating the need for user effort to stop unnecessary notifications.
Solution Approach 2:
The system implements a feedback loop where reminder notifications are sent to the user, and the system continuously monitors for purchase completion signals. When purchase completion is detected through sensor data or user input, the system adjusts its behavior by stopping further reminders. This feedback mechanism ensures reliable reminders are provided while automatically ceasing them when no longer needed, reducing user operation effort.
2Device complexity
If the system sets a fixed reminding period for all articles, then the reminder timing is simple to manage, but the reminder timing is not appropriate for different article categories
Solution Approach 1:
The system assigns different reminding periods to different article categories based on their specific characteristics. For example, perishable goods may have shorter reminding periods while non-perishable items have longer periods. This local quality approach allows the system to maintain relatively simple management while achieving appropriate timing adaptability for each article type, resolving the contradiction between complexity and versatility.
Solution Approach 2:
The system dynamically adjusts the reminding period parameter based on the article category. When an article is registered, the system automatically selects or sets an appropriate reminding period based on pre-defined categories and their characteristics. This parameter change strategy enables the system to adapt reminder timing to different article types without requiring complex manual configuration, balancing management simplicity with timing appropriateness.
Data Source
AI summary
An information processing method includes a step of obtaining article information including a category of an article which a user wishes to purchase, and a step of outputting a reminder concerning purchase of the article, when a reminding condition is satisfied in a reminding period that is set according to the category of the article obtained.