Beacon Data Collection Configuration for Mobile Devices
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Solution Overview
Problem
Existing beacon data collection methods often result in the transmission of erroneous or irrelevant data, leading to inefficiencies and increased power consumption, as mobile devices continuously collect and send data without considering user or device context.
Innovation Solution
The proposed solution involves adjusting and scheduling beacon data collection based on user or device context to enhance crowdsourcing efficiency and accuracy, by determining a specific configuration for data collection that takes into account factors such as motion state, location relative to the user, and activity, thereby reducing irrelevant data transmission and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If mobile devices continuously collect and send beacon data, then data quantity increases, but power consumption increases and data accuracy decreases
Solution Approach 1:
The system implements periodic scanning techniques where mobile devices perform scans at scheduled intervals rather than continuously, sampling beacon data at discrete time points. This periodic approach reduces power consumption while maintaining adequate data collection for mapping beacon positions within indoor environments.
Solution Approach 2:
The system enables mobile devices to autonomously determine whether to collect and transmit beacon data based on contextual factors such as movement detection, location stability, and proximity to known beacons. This self-service mechanism allows devices to intelligently skip data collection when conditions indicate low value, reducing overall power consumption across the network.
2Quantity of substance
If mobile devices continuously collect and send beacon data, then data coverage increases, but data reliability decreases
Solution Approach 1:
The system changes operational parameters of beacon data collection based on detected context conditions. When a mobile device is detected to be moving or in contexts where accurate location tagging is difficult, the system adjusts collection parameters to skip or reduce data gathering, thereby maintaining higher reliability of the collected dataset.
Solution Approach 2:
The system incorporates feedback mechanisms where mobile devices report contextual information (such as movement status, location stability, and environmental conditions) that is used to dynamically adjust data collection behavior. This feedback loop ensures that data is primarily collected when conditions favor high accuracy and reliability.
3Quantity of substance
If mobile devices send all collected beacon data, then data completeness increases, but transmission efficiency decreases
Solution Approach 1:
The system extracts and transmits only the most relevant beacon data to the server, filtering out redundant or low-value measurements. By selectively extracting data that meets quality thresholds and contextual relevance criteria, the system maintains data completeness for useful information while significantly reducing unnecessary transmission overhead.
4Use of energy by moving object
If mobile devices perform periodic scans to sample beacon data, then power consumption decreases, but measurement precision decreases
Solution Approach 1:
The system dynamically adjusts the scanning interval and data collection frequency based on contextual conditions. When a mobile device is stationary and conditions favor accurate measurement, the system increases scanning frequency to improve precision. When the device is moving or conditions are unfavorable, the system reduces scanning frequency to conserve power, accepting lower precision in those contexts.
Data Source
AI summary
Method, mobile device, computer program product, and apparatus relating to beacon data collection. A user context at a mobile device may be obtained and a recommended configuration for beacon data collection can be determined according to the recommended configuration. A reliability metric may be determined as part of determining the recommended beacon collection configuration. The beacon data collection may include filter or weight to define when or how to send or collect beacon data and/or positioning data.