Passive Wireless Temperature Sensing With RF Impedance Compensation
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Solution Overview
Problem
Current wireless communication systems, particularly RFID systems, face challenges in accurately processing and transmitting environmental sensed conditions due to variations in RF signal strength and impedance changes caused by environmental factors, which affect the reliability and precision of data collection.
Innovation Solution
The implementation of sensor computing devices that communicate with passive wireless sensors to adjust RF signal power levels and compensate for impedance changes, using back-scattering techniques to generate coded values representing environmental conditions, and processing these values to determine accurate measures of sensed conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If RF signal strength varies due to environmental factors, then wireless communication coverage is extended, but measurement precision of environmental conditions deteriorates
Solution Approach 1:
The system measures the RF signal strength at the sensor and feeds this information back to the computing device. The computing device uses this feedback to calculate compensation values that correct the environmental condition measurements, thereby maintaining measurement precision despite variations in RF signal strength caused by environmental factors or changes in wireless communication coverage area.
Solution Approach 2:
The system changes the parameter being measured from raw environmental data to compensated environmental data. By calculating compensation values based on RF signal strength measurements and applying these to the environmental condition readings, the system adjusts the measurement parameters to account for RF variability, thus maintaining precision across different coverage areas.
2Adaptability or versatility
If impedance changes occur due to environmental factors, then sensor adaptability to different environments is improved, but reliability of data transmission deteriorates
Solution Approach 1:
The sensor measures impedance changes caused by environmental factors and provides feedback to the computing device. The computing device uses this impedance information to adjust compensation calculations, thereby maintaining data transmission reliability despite the sensor's adaptability to different environmental conditions.
Solution Approach 2:
The RF signal strength measurement acts as an intermediary parameter that mediates between impedance changes and data transmission reliability. By using RF signal strength as an intermediate measurement, the system can compensate for impedance variations caused by environmental adaptability, thus maintaining reliable data transmission across different environments.
3Device complexity
If back-scattering techniques are used to generate coded values, then device complexity is reduced, but loss of information increases
Solution Approach 1:
The computing device receives coded values from the passive sensor via back-scattering and uses RF signal strength feedback to calculate compensation values. This feedback mechanism allows the system to recover information that would otherwise be lost due to the simplified back-scattering encoding scheme, maintaining environmental condition information accuracy without increasing sensor device complexity.
Solution Approach 2:
The system replaces complex active sensing electronics with passive back-scattering mechanics. The passive sensor modulates RF signals through back-scattering without requiring active transmission components, reducing device complexity. The computing device compensates for the information loss through signal processing and compensation calculations based on RF signal strength measurements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables real-time, accurate monitoring and processing of environmental conditions such as moisture, temperature, and humidity, improving data reliability and precision across multiple locations through efficient communication and calibration protocols.
Implementation Method 1
using back-scattering techniques to generate coded values representing environmental conditions
Data Source
AI summary
A passive wireless temperature sensor includes a radio frequency (RF) front end having a variable input impedance. The RF front end includes an antenna operable to receive an RF signal having a particular carrier frequency and a tuning circuit having a resonant frequency corresponding to the particular carrier frequency. The passive wireless temperature sensor further includes one or more temperature sensing elements coupled to the RF front end. When sensing a temperature, the one or more temperature sensing elements cause a change in the variable input impedance. The passive wireless temperature sensor further includes a processing module operably coupled to the RF front end operable to adjust the resonant frequency of the tuning circuit to compensate for the change in the variable input impedance and generate a coded value representative of the change. The coded value representative of the change corresponds to the sensed temperature.