Audio-Visual Beehive Pest Detection for Automated Entry Denial
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Solution Overview
Problem
Current pest management in apiaries is largely reactionary, failing to prevent pest entry into beehives effectively, and labor-intensive inspections are impractical for timely detection and control of invasive species.
Innovation Solution
A system and apparatus using visual and audio classification sensors mounted on beehives to identify and actively prevent pest entry by employing automated kill mechanisms, leveraging AI algorithms to differentiate between bees and pests, and integrating energy delivery systems to eliminate or injure intruding insects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If labor-intensive manual inspections are used to detect pests, then detection capability is improved, but time consumption and labor requirements increase significantly
Solution Approach 1:
The patent replaces manual visual inspection with automated electronic detection systems including cameras, sensors, and image processing algorithms. These systems automatically detect and identify pests at the hive entrance, eliminating the need for labor-intensive manual inspections while providing continuous monitoring capability.
Solution Approach 2:
The system enables self-detection and self-reporting of pests through automated sensors and algorithms that continuously monitor the hive entrance. The system automatically identifies pest species, counts individuals, and triggers appropriate responses without requiring human intervention for detection tasks.
2Object-generated harmful factors
If reactive pest control measures are taken after pest entry is detected, then pest elimination is achieved, but bee colony losses have already occurred
Solution Approach 1:
The patent implements preliminary protective actions by detecting pests at the hive entrance before they can enter and harm the colony. Automated kill mechanisms such as electrocution grids or compressed air jets eliminate pests preemptively, preventing them from reaching the bees and causing damage.
Solution Approach 2:
The system performs preliminary identification and classification of insects approaching the hive. By categorizing insects as bees or pests before they enter, the system prepares appropriate responses in advance, ensuring that protective actions are already positioned and ready to execute immediately upon pest detection.
3Object-generated harmful factors
If automated kill mechanisms are deployed at hive entrance, then pest entry is prevented effectively, but system complexity increases
Solution Approach 1:
The system segments the pest management function into distinct modular components: detection module (cameras and sensors), classification module (AI algorithms), and execution module (kill mechanisms). This segmentation allows each component to be independently optimized, maintained, and replaced, reducing overall system complexity despite the automated functionality.
Solution Approach 2:
The patent introduces an intermediary classification layer between detection and execution. AI algorithms analyze visual and sensor data to distinguish bees from pests before triggering kill mechanisms. This intermediary step prevents erroneous activation while maintaining automated response capability, managing system complexity through intelligent mediation.
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 system provides real-time pest detection and prevention, reducing bee colony losses by actively denying pest access, enhancing bee health and apiary management efficiency.
Implementation Method 1
electrocution mechanisms that deliver energy to insects to kill or injure them
Data Source
AI summary
Aspects of this disclosure include a system, method and apparatus providing automated audio and vision based pest detection and entry denial for a beehive. The apparatus may include multiple video classification sensors that transmit a signal of the dorsal and lateral aspect of the insects to a computer running a video processing algorithms that classify all insects attempting to enter a beehive. Additionally, the apparatus may include multiple audio classification sensors that transmit audio signals to the computer for audio analysis to assist in classification. Insects classified as pests (not-a-bee) are actively excluded from the beehive.