Wireless Sensor Network Calibration System
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Solution Overview
Problem
Existing wireless sensor networks face challenges in managing events, conserving memory, and configuring node discovery and calibration in multi-node applications, particularly in resource-constrained systems used for physiological health monitoring and industrial applications.
Innovation Solution
A wireless sensor network system that includes a controller communicatively coupled to sensors, capable of calculating calibration values, storing them in memory, and performing node discovery, configuration, and event management, using a method involving sensor calibration based on initial states and contextual event data delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex central monitoring units and complex signal processing are used to manage data from sensor nodes, then data management effectiveness is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent extracts complex signal processing and data management functions from centralized monitoring units and relocates them to individual sensor nodes. Each node performs local calibration, event detection, and data processing independently, eliminating the need for complex central processing while maintaining effective data management through distributed intelligence
Solution Approach 2:
Sensor nodes are designed to be self-calibrating and self-managing. Each node automatically performs calibration using stored calibration values, independently manages its own data processing, and autonomously determines when to transmit data, thereby reducing overall system complexity while maintaining effective operation without requiring complex centralized control
2Adaptability or versatility
If more sensor nodes are deployed throughout the network, then monitoring coverage and system functionality are improved, but memory requirements and power consumption increase
Solution Approach 1:
The patent implements local quality by tailoring the data collection and processing capabilities to the specific needs of each sensor node's location and function. Not all nodes collect or store all types of data; instead, each node selectively manages only the data relevant to its specific monitoring task, reducing overall memory requirements while maintaining comprehensive network functionality
Solution Approach 2:
The system performs preliminary calibration actions at each node during initialization, storing calibration values locally. This preliminary calibration enables nodes to operate independently without requiring extensive memory for ongoing calibration data or complex processing routines, as the calibration parameters are pre-computed and stored efficiently
3Measurement precision
If calibration values are stored in memory for each sensor node, then measurement accuracy is improved, but memory consumption increases
Solution Approach 1:
The patent applies parameter changes by transforming calibration data from raw, high-precision floating-point values into compressed, quantized parameters. Calibration values are stored as reduced-precision data structures that capture the essential calibration information with minimal memory overhead, maintaining measurement accuracy while significantly reducing memory consumption
Data Source
AI summary
A system has at least one sensor and a controller communicatively coupled to the sensor. The system further has logic configured to calculate a calibration value based upon an initial state of the sensor and store the calibration value in memory.