Accelerometer Trajectory Search for Minimal-Input Result Matching
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Solution Overview
Problem
Conventional internet search methods require specific and detailed input, leading to numerous irrelevant results and increased user effort, especially when the search criteria is abstract or uninformed, and they depend on internet connectivity and user interaction.
Innovation Solution
A method that determines a trajectory based on movement data from a client device's accelerometer, incorporating it into facts, comparing to historical data, and providing relevant results with minimal user interaction, leveraging on-device data and advanced neural networks for quick and accurate information retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search methods are used with detailed input, then search specificity is improved, but user effort and time spent sifting through results increases
Solution Approach 1:
The system automatically analyzes accelerometer data to determine device trajectory and infers user intent without requiring manual input. The search system serves itself by autonomously formulating queries based on movement patterns, eliminating the need for users to spend time crafting specific search terms or filtering results.
Solution Approach 2:
The system performs preliminary analysis of accelerometer data to determine device trajectory before the search is executed. By pre-processing movement data and inferring user intent in advance, the system prepares targeted queries that reduce the need for subsequent result filtering and refine search specificity upfront.
2Ease of operation
If conventional search methods are used with abstract input, then ease of operation is improved, but result relevance deteriorates
Solution Approach 1:
Device trajectory data serves as an intermediary that bridges the gap between abstract user actions and specific search intent. The accelerometer-based movement patterns provide additional contextual information that helps the system infer meaningful search queries even when users provide minimal or abstract input, thereby maintaining result relevance.
3Reliability
If conventional search methods are used, then information retrieval capability is improved, but dependency on internet connectivity increases
Solution Approach 1:
The system leverages on-device accelerometer data and local processing capabilities to perform search operations independently of external connectivity. By utilizing self-contained sensors and executing trajectory analysis locally, the system maintains information retrieval capability while reducing dependency on internet infrastructure.
4Adaptability or versatility
If conventional search methods are used, then search coverage is improved, but user interaction requirements increase
Solution Approach 1:
The system replaces manual text input and interaction mechanisms with automatic accelerometer-based trajectory detection. By substituting mechanical user actions (typing, clicking) with automated sensor-based intent inference, the system maintains broad search coverage while dramatically reducing user interaction requirements.
Data Source
AI summary
A method is provided. The method includes determining a trajectory based on movement data from an accelerometer of a client device. In response to the trajectory being within configured limits, the method includes one or more of incorporating the trajectory into one or more facts, each fact including an entity, an observation, and an object, comparing the one or more facts to historical data, and determining one or more closest matches between the one or more facts and the historical data.