Wearable Gesture Detection for Proximate Point-of-Interest Data
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Solution Overview
Problem
Existing wearable computing devices require users to manually search for information about points of interest (POIs) by unlocking their mobile devices and typing search terms, creating a gap between seeing a POI and retrieving associated information.
Innovation Solution
A computing system with sensors, such as an inertial measurement unit (IMU), detects user gestures to identify a particular POI and provides associated data for display, reducing the need for manual search by leveraging pre-existing mapping applications and databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually search for POI information by unlocking mobile devices and typing search terms, then information accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-load- ing POI data and mapping applications into the wearable device before the user needs information. When a POI is detected, the data is already available for immediate display, eliminating the need for manual searching and typing during the user's attention span.
Solution Approach 2:
The wearable device acts as an intermediary between the user and the mobile device. It detects POIs using sensors (camera, GPS, IMU), retrieves pre-loaded data, and displays information without requiring the user to manually interact with the mobile device, thus reducing time consumption while maintaining accuracy.
2Measurement precision
If users manually search for POI information by unlocking mobile devices and typing search terms, then information accuracy is improved, but device operation complexity increases
Solution Approach 1:
The wearable device performs self-service by automatically detecting POIs using its sensors (camera, GPS, IMU), automatically retrieving pre-loaded data, and automatically displaying information. This eliminates the need for users to manually unlock devices, type search terms, or navigate through applications, significantly reducing operational complexity while maintaining information accuracy.
Solution Approach 2:
The system replaces the mechanical manual search process (unlocking, typing, navigating) with an automated sensor-based detection system. The IMU, camera, and GPS automatically detect POIs and trigger data retrieval, substituting complex manual operations with automated electronic sensing and processing.
3Ease of operation
If the system continuously stores all POI data in the wearable device, then information accessibility is improved, but storage space requirements increase
Solution Approach 1:
The system segments POI data into categories (restaurants, attractions, transit stations) and loads only relevant categories into the wearable device based on the user's location and interests. This selective loading maintains high information accessibility for relevant POIs while minimizing storage space consumption by excluding irrelevant data.
Solution Approach 2:
The wearable device stores POI data with local quality by prioritizing and detailed-storing POIs near the user's current location while maintaining a lighter data structure for distant POIs. The system loads detailed information only for POIs within a relevant radius, improving accessibility for nearby interests while conserving storage space for the entire database.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Efficiently and accurately provides contextual information about surroundings by reducing the time and effort needed to obtain POI data, optimizing processor usage, and conserving storage space in computing devices.
Implementation Method 1
A computing system with sensors, such as an inertial measurement unit (IMU), detects user gestures
Data Source
AI summary
Computing systems and computer-implemented methods are provided. In one aspect, the computer-implemented method includes detecting, by a computing system comprising one or more computing devices, a user gesture from a user of the computing system. The computer-implemented method includes, responsive to detecting the user gesture, obtaining, by the computing system, data associated with one or more points of interest (POIs) proximate to a physical location of the user. The computer-implemented method includes determining, by the computing system, the user gesture is directed to a particular POI of the one or more POIs. The computer-implemented method includes providing, by the computing system, data associated with the particular POI for display to the user.