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WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research.

Sajid Nazir1, Scott Newey2,3, R Justin Irvine2

  • 1School of Engineering, University of Aberdeen, Aberdeen, United Kingdom.

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Summary

WiseEye, an open-source camera trap platform, reduces false images in wildlife research. This customizable technology improves data accuracy and processing efficiency for conservation efforts.

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Area of Science:

  • Ecology and Wildlife Management
  • Computer Science and Engineering
  • Sensor Technology

Background:

  • Digital camera traps are widely used in wildlife research but have limitations in control, image generation, and flexibility.
  • Current camera trap technology often leads to user frustration due to inflexibility and large data volumes.

Purpose of the Study:

  • To develop a user-customizable, open-source camera trap platform named 'WiseEye'.
  • To enhance camera trap functionality for wildlife research and conservation management.
  • To reduce false positives and improve data processing efficiency.

Main Methods:

  • Developed WiseEye using a Raspberry Pi single-board computer and compatible peripherals.
  • Implemented a 'confirmatory sensing' concept, using multiple sensor modalities (e.g., Passive Infrared, radar, pixel change) to validate triggers.
  • Incorporated user-definable metadata for image identification and filtering.

Main Results:

  • WiseEye significantly reduced false positive and false negative images compared to a commercial camera trap.
  • Confirmatory sensing and user-definable metadata decreased post-collection image processing time.
  • The platform demonstrated increased value for wildlife research and conservation management.

Conclusions:

  • WiseEye offers a flexible, customizable, and open-source camera trap solution.
  • The confirmatory sensing approach effectively minimizes spurious images, enhancing data reliability.
  • This novel platform represents a significant advancement in camera trap technology for ecological studies.