Smoking Behavior Geofencing to Reduce Repetitive Intervention Prompts
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Solution Overview
Problem
Conventional smoking cessation methods lack accuracy and flexibility in prompting interventions, often occurring at fixed times or locations, leading to ineffective and repetitive prompts due to GPS inaccuracy and disregard for smoking frequency, thus failing to provide a personalized and intelligent intervention.
Innovation Solution
A method and apparatus that analyze user smoking behavior records to determine high-probability smoking locations and times, calculating prompt ranges based on these data to deliver targeted intervention prompts, considering frequency and nicotine dependence, using voice, video, or text prompts tailored to specific times and user needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prompting is performed on the basis of a specific fixed location using GPS, then the intervention can be location-based, but the GPS accuracy is insufficient (about 10 meters) causing repetitive prompts when moving between smoking sites
Solution Approach 1:
The patent creates a prompt range (geofence) around each smoking site rather than using a single fixed location point. This local quality approach allows the system to define a specific spatial zone with customized prompting rules, reducing false triggers when users move between nearby smoking sites while maintaining location-based intervention effectiveness.
Solution Approach 2:
The patent segments the monitoring area into multiple prompt ranges around different smoking sites. By dividing the space into distinct zones with calculated distances between them, the system可以避免 repetitive prompts and provides more precise location-based intervention.
2Adaptability or versatility
If prompting is performed on the basis of a specific fixed location, then location-based intervention is achieved, but smoking frequency is not considered causing excessive prompting that degrades effectiveness
Solution Approach 1:
The patent dynamically adjusts prompting strategies based on user smoking frequency and behavior patterns. The system learns from historical data and adapts the prompting frequency and timing, transitioning from static fixed-location prompting to dynamic behavior-based prompting that considers individual user habits and nicotine dependence levels.
Solution Approach 2:
The patent implements a feedback mechanism that monitors user responses to prompts and smoking behavior patterns. This feedback is used to continuously optimize prompting strategies, adjusting the frequency and timing of interventions based on what works best for each individual user, thereby improving overall prompt effectiveness.
3Ease of operation
If conventional fixed-time or fixed-location prompting is used, then the system is simple to operate, but it cannot achieve accurate and intelligent intervention based on user smoking habits
Solution Approach 1:
The patent enables the system to automatically learn and adapt to user smoking patterns without requiring manual configuration. The system self-adjusts by analyzing historical smoking data, identifying personal smoking sites and time patterns, and autonomously optimizing prompting strategies, thereby maintaining ease of operation while achieving high personalization.
Solution Approach 2:
The patent performs preliminary analysis of user smoking behavior during an initial learning period to establish baseline patterns before full intervention begins. This preliminary action allows the system to pre-configure personalized prompt ranges and timing based on observed habits, enabling accurate intervention from the start while keeping the user interface simple.
Data Source
AI summary
The present disclosure provides a triggering method of an intervention prompt on the basis of user smoking behavior records, comprising: receiving smoking behavior record data associated with a user, wherein the smoking behavior record data includes a plurality of smoking behavior records; analyzing the smoking behavior record data to determine smoking behavior location data associated with each of the plurality of smoking behavior records; calculating a distance between locations indicated by every two smoking behavior location data; recording a first number of smoking behavior records in which the distance is less than a first distance as a set of smoking behavior record data; in a case where the first number is greater than a first threshold, determining a prompt range on the basis of the smoking behavior location data associated with the set of smoking behavior record data, wherein the prompt range includes consecutive areas or spaces that are connected and further includes locations indicated by the respective smoking behavior location data associated with the set of smoking behavior record data; and triggering pushing of the intervention prompt if the user enters the prompt range from the outside.