Low-Power Capacitive Pest Detection with Sensor-Triggered Recalibration
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Solution Overview
Problem
Existing pest detection devices using capacitive sensing face challenges in accurately detecting small pests and require frequent recalibration, which significantly reduces battery life.
Innovation Solution
Incorporating secondary sensors to monitor environmental conditions and trigger capacitive sensor recalibration only when necessary, reducing the frequency of recalibrations and conserving battery power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous or near-continuous recalibration is performed to maintain sensing accuracy, then measurement precision is improved, but use of energy increases and battery life is reduced
Solution Approach 1:
The system performs recalibration periodically or at specific intervals rather than continuously, using a timer or schedule-based approach to trigger recalibration events. This reduces energy consumption while maintaining acceptable accuracy by recalibrating at predetermined time intervals or under specific conditions.
Solution Approach 2:
The system uses feedback from environmental sensors (temperature, humidity, light) to determine when recalibration is actually needed. When environmental conditions change beyond certain thresholds, the system triggers recalibration; otherwise, it maintains current calibration settings, optimizing the balance between accuracy and energy consumption.
2Measurement precision
If the capacitive sensor is made more sensitive to detect smaller pests, then measurement precision is improved, but the sensor becomes more susceptible to environmental interference and false activations
Solution Approach 1:
Environmental sensors act as intermediaries between the capacitive sensor and the detection logic. These sensors monitor temperature, humidity, and light conditions, and their data is used to adjust the capacitive sensor's sensitivity or to filter out false readings caused by environmental changes, allowing the system to maintain high sensitivity without increased false activations.
Solution Approach 2:
The system dynamically changes the operating parameters of the capacitive sensor based on environmental conditions. When environmental interference is detected, the system adjusts sensitivity thresholds, sampling rates, or filtering parameters to maintain accurate pest detection while compensating for environmental factors.
3Adaptability or versatility
If the sensor is designed to detect a wide range of pest sizes, then adaptability is improved, but device complexity increases
Solution Approach 1:
The capacitive sensor is designed with a universal detection capability that can sense a wide range of pest sizes using a single sensor element. The system uses adjustable sensitivity ranges and multiple detection thresholds to detect everything from small insects to larger pests, eliminating the need for multiple specialized sensors and reducing overall device complexity.
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
Enhances pest detection accuracy for small pests while significantly extending battery life by minimizing unnecessary recalibrations.
Implementation Method 1
an electronic sensor that detects the presence of a pest by measuring a change in capacitance due to a pest's presence on a capacitive sensor
Data Source
AI summary
Various examples are directed to apparatus and methods for enhanced pest detection and enhanced battery life for a power supply of a pest detection device. The pest detection device includes a capacitive sensor configured to detect a presence of one or more pests, and one or more secondary sensors configured to detect one or more prescribed conditions. The pest detection device also includes a controller connected to the capacitive sensor and the one or more secondary sensors. The controller is configured to initiate calibration of the capacitive sensor based at least in part on one or more signals received from the one or more secondary sensors.