Light Trap Camera Monitoring for Automated Insect Counting
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Solution Overview
Problem
Current flying insect light traps rely on manual counting and infrequent inspections, leading to time-consuming, inaccurate data collection and delayed response to high pest activity, limiting the effectiveness of remediation efforts.
Innovation Solution
Integration of a camera-based monitoring device with a computer vision algorithm that automatically takes and processes images of glue boards in flying insect light traps, enabling frequent, accurate insect counting and classification, and remote data transmission for real-time monitoring and alerting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual counting and infrequent inspections are used, then device complexity is reduced, but measurement precision and productivity deteriorate
Solution Approach 1:
The patent replaces the manual mechanical counting process with an automated optical system. A camera captures images of the glue board, and computer vision algorithms automatically count and classify insects, eliminating the need for manual inspection while significantly improving counting accuracy and enabling frequent monitoring without increasing overall system complexity.
Solution Approach 2:
The patent uses digital image copies of the glue board as a surrogate for direct manual counting. The camera creates visual replicas of the insect-trapped glue board, which can then be analyzed automatically by image processing algorithms, enabling precise measurement without physical contact or manual handling.
2Device complexity
If manual inspection is used, then device complexity is reduced, but loss of time increases
Solution Approach 1:
The patent implements continuous automated monitoring by having the camera take images at predetermined time intervals (e.g., hourly or daily). This continuous action replaces intermittent manual inspections, ensuring that pest activity is detected promptly and that response time is minimized while maintaining simple device architecture.
Solution Approach 2:
The monitoring system performs self-service by automatically capturing images, processing them through image recognition algorithms, and generating counts without human intervention. This automation eliminates the time loss associated with manual inspection scheduling and execution while keeping the device relatively simple.
3Productivity
If frequent monitoring is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The patent employs periodic action by configuring the camera to capture images at predetermined time intervals rather than continuously. This approach enables frequent monitoring (improving productivity) while allowing the system to remain dormant between captures, thereby minimizing energy consumption from the camera, processor, and communications module.
Solution Approach 2:
The monitoring frequency is made dynamic and adjustable based on pest activity levels and client requirements. The system can adapt its imaging schedule, increasing frequency when high activity is detected and reducing it during low-activity periods, thus optimizing the balance between productivity and energy usage.
Data Source
AI summary
A flying insect light trap monitoring device and related methods and systems. The flying insect light trap monitoring device includes a housing, camera, controller, and communications module. The housing includes a mounting structure configured to couple with a flying insect light trap. The camera generally includes a wide angle lens. The camera and wide angle lens are secured to the housing and take a digital photograph image of a glue board in the flying insect light trap. The controller, including a processor and a memory, is secured within the housing and is communicatively coupled to the camera. The controller receives the digital photograph image. The communications module is operatively coupled with the controller and sends data packets, including the digital photograph image, to a remote server. Further, an image processing engine that processes the image and generates an insect count can be included.