Adaptive Sensor Sampling for Data Quality and Power Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems with remotely located sensors face inefficiencies in collecting and transmitting data due to the lack of effective methods for managing data signal quality and sampling density, leading to suboptimal power and bandwidth usage.
Innovation Solution
A method and apparatus that receive data signals from sensors, determine their quality, and provide feedback signals to control the sampling basis and density, utilizing compressive sampling to efficiently capture and transmit sparse data signals, allowing for adaptive adjustment of sampling parameters based on signal sparsity thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors continuously transmit data at highest sampling density, then data quality is maintained, but power and bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts sampling density based on signal characteristics and quality metrics. Sensors transition between different sampling rates (e.g., highest density, reduced density, lowest density) according to real-time conditions, allowing power consumption to vary with actual data quality requirements rather than operating at maximum density continuously
Solution Approach 2:
The system changes sampling parameters (density, rate) based on determined signal quality and sparsity thresholds. When signal quality exceeds thresholds, sampling density is reduced; when quality falls below thresholds, sampling density increases, thereby adapting power consumption to actual measurement needs while maintaining data quality
2Loss of information
If sensors transmit all captured data, then complete information is provided, but bandwidth consumption increases
Solution Approach 1:
The system extracts and transmits only the most relevant data based on quality metrics and sparsity analysis. Instead of transmitting all captured data, sensors identify and prioritize transmission of data points that exceed quality thresholds or represent significant changes, thereby reducing bandwidth consumption while maintaining information completeness for critical measurements
Solution Approach 2:
The system transmits partial data sets based on quality thresholds rather than complete data sets. When signal quality is sufficient, only essential data points are transmitted; when quality degrades, more data points are transmitted to ensure information completeness, implementing a threshold-based partial transmission strategy
3Measurement precision
If sampling density is increased, then data accuracy is improved, but power and bandwidth usage increases
Solution Approach 1:
The system implements dynamic sampling density adjustment where sensors switch between high, medium, and low sampling rates based on real-time quality assessments. This allows the system to maintain high data accuracy when needed while improving power and bandwidth efficiency during periods when lower sampling density suffices, optimizing the trade-off between accuracy and resource consumption
Data Source
AI summary
A system comprising: at least one sensor and at least one control apparatus wherein; the sensor comprises: at least one processor; and at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform; compressing a sensor data signal using a sampling basis to obtain a compressed data signal; and in response to a first feedback signal changing a sampling basis used to obtain the compressed data signal; and wherein the control apparatus comprises: at least one processor; and at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform; receiving the data signal from the at least one sensor; determining a quality of the received data signal; and if the quality of the received data signal is within a first threshold providing a feedback signal to control the sampling basis of the sensor.