Context-Based Mobile Beacon Activation
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Solution Overview
Problem
Current standalone beacon devices are costly, require frequent battery monitoring, waste battery life due to continuous transmission, and are prone to theft and excessive notifications, while existing mobile devices are not efficiently utilized for beacon functions.
Innovation Solution
A computer-implemented method that identifies and activates mobile devices to listen for or emit beacon signals based on context, using context-based rules to optimize beacon functionality, thereby reducing unnecessary battery drain and leveraging existing mobile devices for cost-effective and efficient beacon operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standalone beacon devices are used continuously, then beacon coverage and availability are improved, but battery life is wasted due to continuous transmission
Solution Approach 1:
The beacon system transitions from continuous transmission to periodic transmission based on context changes. The mobile device monitors context parameters (location, movement, user activity) and only activates beacon transmission when specific context conditions are met, such as when the device enters a designated area or detects user presence, thereby conserving battery life while maintaining reliable beacon availability when needed.
Solution Approach 2:
The mobile device performs self-monitoring of context parameters and autonomously determines when to activate or deactivate beacon transmission without requiring external control. The device evaluates its own location, movement status, and user activity levels to decide whether to transmit beacon signals, enabling energy-efficient autonomous operation.
2Ease of manufacture
If mobile devices are activated to perform beacon functions, then cost is reduced, but device complexity increases due to context monitoring and qualification determination
Solution Approach 1:
The mobile device is designed to perform multiple functions: it serves as both the user's communication device and the beacon transmission device. The existing mobile device hardware and operating system are leveraged to provide beacon capabilities, eliminating the need for separate dedicated beacon devices and reducing overall system cost despite the added complexity of context monitoring.
Solution Approach 2:
The system monitors changes in context parameters (location coordinates, movement velocity, user activity level) to dynamically determine beacon transmission eligibility. By establishing threshold values for these parameters and evaluating their changes over time, the system achieves cost-effective operation through software-based context management rather than hardware complexity.
3Speed
If beacon transmission is activated without context-based rules, then beacon responsiveness is improved, but unwanted notifications increase due to excessive transmission
Solution Approach 1:
The system continuously monitors context parameters and uses this feedback to dynamically control beacon transmission. When context conditions change (e.g., user enters a new location, movement detected, or activity level changes), the system adjusts transmission status accordingly. This feedback mechanism ensures rapid response to genuine user needs while preventing unwanted notifications by suppressing transmission when context indicates inappropriate conditions.
Solution Approach 2:
The beacon transmission characteristics are adjusted based on local context conditions. Different transmission behaviors are applied in different contexts: high responsiveness when user is present and active, reduced transmission when device is stationary or user is inactive. This localized adaptation of transmission quality to specific context conditions eliminates unwanted notifications while maintaining responsiveness when needed.
4Measurement precision
If context monitoring is performed continuously, then beacon accuracy is improved, but processing time and energy consumption increase
Solution Approach 1:
Instead of continuous context monitoring, the system employs periodic monitoring triggered by specific events or time intervals. Context parameters are updated and evaluated at discrete moments when significant changes occur (e.g., location threshold crossed, movement detected, user activity change), achieving accurate context measurement without the processing overhead of continuous monitoring.
Solution Approach 2:
The system skips unnecessary context evaluation by using event-driven architecture. Context monitoring is activated only when specific triggering conditions occur (such as entering a designated area or detecting user presence), rather than continuously evaluating all context parameters. This approach maintains measurement precision for relevant contexts while minimizing processing time and energy consumption during idle periods.
Data Source
AI summary
A computer-implemented method includes identifying a context associated with a mobile device, wherein the mobile device is capable of listening for a beacon signal. The computer-implemented method further includes determining whether the mobile device is qualified to listen for the beacon signal based on the context associated with the mobile device. The computer-implemented method further includes activating the mobile device to listen for the beacon signal.