Animal Deterrance using Computer Vision and Raspberry Pi

DOI

10.2991/978-94-6463-471-6_73How to use a DOI?

Keywords

Animal Deterrence System; YOLOv8 Model; Ultralytics Framework; Computer Vision Algorithms; Raspberry Pi; Real-time Video Analysis; Unauthorized Animal Presence Detection; Deterrent Devices

Abstract

This paper introduces a sophisticated animal deterrence system, employing the YOLOv8 model and the Ultralytics framework. The system, designed to thwart unauthorized animal invasions in restricted areas, integrates cutting-edge computer vision algorithms with the computational capabilities of Raspberry Pi. In real-time, strategically positioned cameras capture video feeds, which are meticulously analyzed using YOLOv8 for precise animal identification and categorization. Upon detecting unauthorized animal presence, the system activates deterrent devices, such as alarms or lights, ensuring swift and effective response. The project’s success pivots on the refinement of computer vision models and seamless Raspberry Pi-to-camera connectivity. Beyond its technical intricacies, the implications of this innovative system are vast, ranging from safeguarding agricultural yields to the preservation of wildlife habitats and the maintenance of urban green spaces. By fostering coexistence and mitigating human-animal conflicts, this project stands as a beacon of innovation in addressing contemporary challenges. The integration of Ultralytics YOLOv8 and tools like Roboflow reflects a strategic and forward-thinking approach in tackling complex real-world issues with efficiency and precision.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ch. Venkata Narayana
AU  - Kundeti Vamsi
AU  - Parsa Pallavi
AU  - Gundepalli Dedeepya
PY  - 2024
DA  - 2024/07/30
TI  - Animal Deterrance using Computer Vision and Raspberry Pi
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 759
EP  - 769
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_73
DO  - 10.2991/978-94-6463-471-6_73
ID  - Narayana2024
ER  -