Augmented Reality Location Scoring System
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Solution Overview
Problem
Existing methods for determining suitable locations for augmented reality game elements in real-world environments do not adequately assess risk and user enjoyment, leading to potential safety hazards and suboptimal gameplay experiences.
Innovation Solution
A system that utilizes geolocation data, user feedback, and moderator input to categorize and prioritize locations for gameplay elements, excluding high-risk areas and adjusting risk scores based on changing conditions, ensuring safe and enjoyable gameplay experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generated elements are placed in high-traffic real-world locations to increase user engagement, then user enjoyment is improved, but user safety deteriorates due to potential risks
Solution Approach 1:
The system performs preliminary risk assessment and location classification before placing generated elements. By pre-evaluating locations using geolocation data, imagery analysis, and risk criteria, the system identifies safe high-traffic areas in advance, allowing user engagement to be maximized without compromising safety.
Solution Approach 2:
The system continuously monitors user interactions and location conditions, using feedback to dynamically adjust element placement decisions. User feedback mechanisms allow the system to learn from actual gameplay experiences and refine its risk assessment models, improving both safety and enjoyment over time.
2Object-affected harmful factors
If comprehensive risk assessment criteria are applied to evaluate location suitability, then user safety is improved, but system complexity increases
Solution Approach 1:
The risk assessment system is divided into modular components: geolocation data processing, imagery analysis, risk criterion evaluation, and location classification modules. Each module handles a specific aspect of the assessment independently, making the complex system manageable and maintainable while comprehensively evaluating safety.
Solution Approach 2:
The system introduces an intermediary classification layer that translates complex risk assessments into simplified location categories (safe, risky, excluded). This intermediary representation simplifies downstream decision-making while maintaining the comprehensiveness of the original risk evaluation.
3Measurement precision
If existing classification methods are used to determine location risk levels, then processing speed is maintained, but assessment accuracy deteriorates due to insufficient consideration of user enjoyment factors
Solution Approach 1:
The system merges multiple data sources (geolocation data, imagery analysis, user feedback) and assessment dimensions (safety risks, user enjoyment factors) into a unified location evaluation framework. This comprehensive approach improves assessment accuracy while the modular architecture maintains processing efficiency through parallel evaluation of different factors.
Data Source
AI summary
The present concepts relate to placing gameplay locations in the real world, where gameplay elements can be generated at the gameplay locations. One example categorizes types of physical elements described in geolocation data, and determines scores for the physical elements based on the categorizations. Gameplay locations can then be utilized according to the scores, and the scores can be continuously refined through user or moderator interaction with gameplay elements that may be generated at the gameplay locations.