Enhancing Pest Monitoring with Digital Simulations

Generating synthetic data allows for cost avoidance and a reduction in time spent on routine tasks

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About the client

Our client, a leading provider of advanced optical equipment, aimed to upgrade their pest monitoring system for industrial spaces such as warehouses. Previously, monitoring pest activity required manual inspection, which was time-consuming and prone to human error. The client sought to modernize this process with a camera system that could automatically identify pests and generate reports.

Business challenge

The main challenge was teaching the new system to recognize different types of insects and detect activity in various conditions. Instead of gathering real-world data, which would be costly and take time, the client needed an efficient way to train the system using simulated, but realistic, data.

Team composition

  • Electronics and Camera Systems Engineers
  • 3D Modeling and Environment Simulation Experts

Our solution

Our team focused on generating synthetic data that could effectively train the system to recognize and track insect activity.

  1. Digital Reconstruction:
    We created a highly detailed digital version of the physical environment, including precise 3D models of the equipment and space. This allowed us to simulate real conditions where the camera system would operate.
  2. Camera Simulation:
    We replicated the camera’s exact position and visual settings to ensure the synthetic data closely matched real-world footage. This was crucial for training the system to accurately identify insects.
  3. Lighting and Environmental Simulation:
    Different lighting scenarios were recreated digitally to simulate varying warehouse conditions, ensuring the system could adapt to different environments and still perform effectively.
  4. Data Rendering:
    Using the simulated environment and camera settings, we generated the data needed for the system to learn how to detect and classify different insect types.

Technologies used in this project

  • 3D Modeling and Rendering: Autodesk 3ds Max, V-Ray, Substance Painter
  • Game Engine: Unreal Engine
  • Graphic Design: Adobe Photoshop
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Value we added

By generating synthetic data, we helped the client avoid the time and expense of capturing real insect images. This solution allowed for faster development and more reliable pest monitoring. The new system reduced the need for manual checks and improved accuracy, making it easier for warehouse operators to monitor pest activity and respond quickly.

Future perspective

This successful project lays the groundwork for future innovations. With the data pipeline in place, the client can further refine their product and expand into other automated monitoring solutions.