Passive RF Sensor Resonance Tuning for Accurate Environmental Sensing
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Solution Overview
Problem
Current wireless communication systems, particularly in RFID systems, face challenges in accurately sensing and processing environmental conditions in real-time across multiple locations due to limitations in data transmission and processing capabilities of passive wireless sensors.
Innovation Solution
The implementation of sensor computing devices and passive wireless sensors that utilize RF receiving circuits with adjustable components to sense environmental conditions, process data, and communicate through wireless communication systems, enabling accurate measurement and real-time monitoring of conditions such as moisture, temperature, and humidity across various locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If passive wireless sensors are used for environmental sensing, then device complexity is reduced, but measurement precision and real-time data processing capability deteriorate
Solution Approach 1:
The system divides sensing functions into two segments: passive wireless sensors for simple environmental parameter detection (temperature, humidity, moisture) and sensor computing devices for advanced data processing and analysis. This segmentation allows each component to be optimized independently, maintaining low overall system complexity while achieving high measurement precision through the computing device's processing capabilities.
Solution Approach 2:
The sensor computing device acts as an intermediary between passive wireless sensors and the central system. It receives raw data from multiple passive sensors, performs local processing and filtering to enhance measurement precision, then transmits processed results to the central system, thereby resolving the contradiction between simple sensor design and accurate measurement.
2Area of stationary object
If passive wireless sensors are deployed across multiple locations, then monitoring coverage is improved, but data transmission and processing capability deteriorates
Solution Approach 1:
The system segments data processing tasks across multiple levels: passive sensors at deployment locations perform minimal local sensing, sensor computing devices at intermediate locations perform local data aggregation and preprocessing, and the central system performs comprehensive analysis. This segmentation enables wide geographic coverage while maintaining processing efficiency by distributing computational loads appropriately.
Solution Approach 2:
Passive wireless sensors perform only the minimal sensing function required, transmitting raw data without attempting complex processing. This partial action approach allows numerous sensors to be deployed across wide areas without overwhelming the system, as each sensor contributes only essential measurements that are processed collectively by sensor computing devices.
3Productivity
If real-time environmental monitoring is implemented, then operational efficiency is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic sampling of environmental conditions by passive wireless sensors rather than continuous monitoring. Sensors take measurements at predetermined intervals, reducing energy consumption while still providing timely environmental data. Sensor computing devices then process these periodic measurements to detect trends and trigger alerts when necessary, maintaining operational efficiency without requiring constant high-energy operation.
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 efficient and accurate real-time monitoring and data processing of environmental conditions, facilitating improved operational efficiency in manufacturing and other applications by providing reliable and scalable wireless communication systems for sensing and data transmission.
Implementation Method 1
the impedance of the plurality of components establishes a resonant frequency of the RF receiving circuit
Implementation Method 2
A sensing element of the wireless sensor is proximally positioned with respect to the RF receiving circuit and to sense an environmental condition
Data Source
AI summary
A wireless communication system includes a plurality of wireless sensors. A wireless sensor includes a radio frequency (RF) receiving circuit, and a sensing element, where the sensing element affects the resonant frequency of the RF receiving circuit. The wireless sensor further includes a processing module operable to determine a first value for an adjustable element of a plurality of elements for a known environmental condition, a second value for the adjustable element for an unknown environmental condition, a difference between the first and second values that corresponds to a change, and to generate a coded value representative of the change. The wireless communication system further includes one or more sensor computing devices coupled to the plurality of wireless sensors via a network. A sensor computing device includes a second processing module operable to receive the coded value and determine a sensed environmental condition based on the coded value.