Sensor Data Selection Using Value of Information and User Preferences
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Solution Overview
Problem
Users are hesitant to share data from sensors due to privacy concerns, power consumption, and annoyance, leading to interruptions and increased costs, especially in applications like traffic monitoring where data from multiple users is needed to improve system modeling.
Innovation Solution
Implementing a system that allows users to define data sharing preferences, where data is requested based on a demand-weighted value of information and user-defined constraints, ensuring privacy and resource efficiency while providing incentives for data sharing, such as access to restricted services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is requested from sensors to improve modeling accuracy, then measurement precision is improved, but user privacy is compromised and resource consumption increases
Solution Approach 1:
The system dynamically adjusts data collection strategies by continuously monitoring user preferences and context, switching between aggressive and conservative data gathering approaches based on real-time conditions, thereby maintaining modeling accuracy while adapting to user privacy concerns
Solution Approach 2:
Different data collection strategies are applied to different users and contexts based on their specific preferences and situations, allowing the system to optimize between accuracy and privacy for each individual case rather than applying a uniform approach
2Measurement precision
If continuous data monitoring is implemented to improve system modeling, then measurement precision is improved, but power consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system employs periodic sampling and event-triggered data collection, where sensors are activated only when specific conditions are met or at predetermined intervals, significantly reducing power consumption while maintaining adequate modeling accuracy
Solution Approach 2:
The monitoring intensity is dynamically adjusted based on current conditions, transitioning between high-frequency sampling during critical events and low-frequency or idle monitoring during stable periods, optimizing the balance between accuracy and energy usage
3Measurement precision
If frequent data requests are made to improve data freshness, then measurement precision is improved, but user annoyance increases
Solution Approach 1:
The system implements periodic data collection at optimized intervals rather than continuous or frequent requests, balancing the need for fresh data with user convenience by sampling at strategically determined times that maintain accuracy while minimizing disruption
Solution Approach 2:
User preferences and responses are continuously fed back into the system to adjust data collection frequency and timing, allowing the system to learn optimal sampling intervals that satisfy both accuracy requirements and user comfort preferences
4Measurement precision
If comprehensive data collection is implemented to improve modeling, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The data collection system is segmented into modular components that can be independently activated based on needs, allowing the system to maintain high accuracy for critical parameters while simplifying the overall architecture by only activating necessary collection modules
Solution Approach 2:
The system dynamically configures the complexity of data collection based on current requirements, simplifying operations during normal conditions and activating comprehensive monitoring only when high accuracy is required, thereby reducing average system complexity
Data Source
AI summary
A method disclosed herein includes the act of computing a value of information for obtaining data from a personal sensor of a user for utilization in a utilitarian computing application, wherein a mobile computing device comprises the personal sensor of the user. The method further includes the act of requesting that the mobile computing device transmit a data packet to the computing device based at least in part upon the value of information for obtaining data from the personal sensor of the user.