Thermal Imaging Animal Detection with Machine Learning Discrimination
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Solution Overview
Problem
Current pest detection technologies lack discrimination and are prone to false positives, leading to inefficient pest management and high operational costs due to inaccurate data, and they do not provide sufficient behavioral information to address the underlying issues.
Innovation Solution
A detection apparatus that uses a thermal imaging camera, microcontroller unit, and computing means with machine learning algorithms to identify and report the presence of warm-blooded animals, including rodents, with real-time data transmission and power management to extend battery life, allowing for precise monitoring and efficient management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor technologies are used for pest detection, then the detection coverage is broad, but the discrimination accuracy is poor leading to false positives
Solution Approach 1:
The patent combines multiple sensor types (thermal imaging camera, motion sensor, ultrasonic sensor) into a single integrated detection apparatus. This merging of complementary sensors enables the system to achieve high discrimination accuracy through multi-parameter analysis while maintaining manageable system complexity through unified hardware architecture and coordinated software processing.
Solution Approach 2:
The detection apparatus is designed as a multi-functional system that can detect various pest types (rodents, birds, mammals) using different sensor modalities. The universal design allows a single device to perform multiple detection functions, improving accuracy across different target species without requiring separate specialized devices for each pest type.
2Reliability
If continuous monitoring is implemented to improve detection reliability, then the detection reliability increases, but the battery power consumption increases
Solution Approach 1:
The system implements periodic monitoring cycles rather than continuous operation. The microcontroller alternates between sleep mode and active detection mode, waking up periodically to check sensor data. This periodic action maintains detection reliability by regularly monitoring the environment while dramatically reducing average power consumption compared to continuous monitoring.
Solution Approach 2:
The detection apparatus dynamically adjusts its operational state based on environmental conditions and detection history. The system transitions between low-power sleep mode and high-power active monitoring mode, and can adjust the frequency and duration of active periods based on whether the area is currently occupied by pests, optimizing the balance between reliability and energy consumption.
3Productivity
If detailed behavioral information is collected to address causative problems, then the pest management effectiveness improves, but the data processing complexity increases
Solution Approach 1:
The system extracts and focuses on specific behavioral parameters that are most indicative of pest presence and activity patterns. Rather than collecting all possible sensor data, the system selectively extracts key features such as thermal signature characteristics, movement patterns, and temporal activity cycles. This extraction approach enables effective pest management analysis while keeping data processing complexity manageable by filtering out irrelevant information.
Solution Approach 2:
The system implements feedback mechanisms where detected behavioral patterns trigger specific management actions and adjust future monitoring strategies. The microcontroller analyzes detected behaviors and provides feedback to modify detection parameters, alert thresholds, and communication triggers. This feedback loop enables progressively more effective pest management while distributing processing complexity across multiple decision-making layers rather than requiring a single complex processing system.
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
The solution enables accurate and efficient detection of warm-blooded animals, reducing false positives, conserving battery life, and providing actionable data for improved pest management, even in areas with limited access to electricity and Wi-Fi.
Implementation Method 1
a thermal imaging camera (50), positioned so as to detect the warm-blooded animal (300) in the detection zone (20)
Data Source
AI summary
A detection apparatus for identifying the presence of a target warm blooded animal in a detection zone and a method of detecting a warm-blooded animal are disclosed. The detection apparatus utilizes a thermal imaging camera, a sensor, and a microcontroller to capture data on an array and interpret data, and a signaller for sending data indicating the presence of a target animal.