Context-Aware Participatory Sensing Energy Management
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Solution Overview
Problem
Context-aware participatory sensing on smartphones faces challenges in energy management, quality of information (QoI) delivery, and revenue generation due to limited battery life, distributed nature of smartphone usage, and human behavior influences, which existing technologies have not adequately addressed.
Innovation Solution
A QoI-aware energy-efficient network management scheme using the Gur Game framework to optimize energy consumption and QoI delivery, where smartphone users make distributed decisions based on credit and energy consumption, and network operators adjust pricing to maximize revenue and ensure satisfactory QoI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If smartphone users continuously capture contextual information to improve QoI delivery, then information quality is improved, but energy consumption increases significantly
Solution Approach 1:
The patent implements dynamic sensor management where the system adaptively adjusts sensor activation and data collection frequency based on real-time conditions. The sensor manager module monitors energy levels, QoI requirements, and contextual relevance to dynamically decide which sensors to activate and at what intensity, resolving the contradiction between continuous monitoring and energy conservation.
Solution Approach 2:
The system changes operational parameters such as sampling rate, sensor activation state, and data transmission frequency based on current needs. When QoI requirements are met or energy is low, the system reduces these parameters; when higher quality is needed or energy is abundant, parameters are increased, thus balancing QoI and energy consumption.
2Reliability
If smartphone users participate in more sensing tasks to improve QoI, then information quality is improved, but energy reserve decreases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors energy reserve levels and QoI achievement. Based on this feedback, the sensor manager adjusts task participation decisions, selecting tasks that meet QoI requirements while staying within energy constraints. The system learns from past performance to optimize future task selection and resource allocation.
3Use of energy by moving object
If the system implements centralized control to optimize energy management, then energy efficiency is improved, but device complexity and user autonomy increase
Solution Approach 1:
The patent implements a self-service approach where each smartphone device autonomously manages its own sensor resources and task participation decisions. The sensor manager module on each device independently evaluates local conditions, energy state, and task requirements to make optimization decisions without requiring centralized control, thus maintaining energy efficiency while reducing system complexity and preserving user autonomy.
4Use of energy by moving object
If sensors are shut down to save energy, then energy consumption is reduced, but quality of information delivered deteriorates
Solution Approach 1:
The patent applies partial action by selectively activating only the necessary sensors and data collection mechanisms required to meet current QoI requirements. Instead of shutting down all sensors or keeping them all active, the system activates only the subset needed for the current task and conditions, thus saving energy while maintaining sufficient information quality. The system can scale up activation if QoI requirements increase.
Data Source
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AI summary
The invention provides a method of processing contextual information over a mobile communication network having a data processing unit, wherein the method comprises the steps of: a) sending a query including information requirement by a first mobile device to the data processing unit, wherein the information requirement comprises at least one information requirement attribute, b) forwarding the query to a plurality of second mobile devices by the data processing unit, wherein the plurality of second mobile devices are identified according to the information requirement of the query, c) deciding on participation by the plurality of second mobile devices using the Gur Game, recommending information property of the contextual information by each of second mobile device respectively, and generating a reply for the query from each of the participants of the plurality of second mobile devices using the Gur Game, wherein the reply is the recommended contextual information and comprises the information property having at least one information attribute, d) accumulating a plurality of replies from the participants of the plurality of the second mobile devices by using the fusion algorithm and calculating a quality of information satisfaction level based on the required information level, by the data processing unit, e) triggering a new round of iteration among the plurality of second mobile devices using the Gur Game, f) sending the fused recommended contextual information to the first mobile device by the data processing unit.