Open Access Open Access  Restricted Access Subscription Access

Leopard Detection and Alert System using YOLOv11 and IoT

Jondhale Satyam Shamrav, Arote Vivek Vikas, Deshmukh Kartik Anil, Kolhal Mayur Sanjay, Ms. K. T. Bhandwalkar

Abstract


The increasing frequency of leopard encounters near human settlements poses critical challenges to public safety and wildlife conservation. This research presents an AI-powered Leopard Detection and Alert System leveraging the YOLOv11 deep learning model and Internet of Things (IoT) technologies. The system performs real-time detection of leopards from surveillance footage and generates instant multi-channel alerts via the Telegram Bot API and an Arduino Uno R3-based piezoelectric buzzer. Experimental results demonstrate detection accuracy with confidence scores of 77–81%, real-time processing at 15–20 FPS, and overall system reliability, making the solution suitable for deployment in forest-border and rural regions. The modular architecture supports future extension to multi-species detection and edge device deployment.


Full Text:

PDF

References


V. Athreya, M. Odden, J. D. C. Linnell, and K. U. Karanth, "Big cats in our backyards: persistence of large carnivores in a human dominated landscape in India," PLOS ONE, vol. 8, no. 3, p. e57872, 2013.

S. Karanth and J. D. C. Linnell, "Human–wildlife conflict: A review of status and mitigation strategies in India," Oryx, vol. 55, no. 4, pp. 546–556, 2021.

Ultralytics Inc., "YOLOv11: Next-Generation Real-Time Object Detector," Ultralytics Open-Source Repository, 2024. [Online]. Available: https://github.com/ultralytics/ultralytics

L. Luo, Y. Liu, and Q. Wang, "A survey on deep learning-based object detection for wildlife monitoring," IEEE Access, vol. 9, pp. 112340–112360, 2021.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, "ImageNet classification with deep convolutional neural networks," Commun. ACM, vol. 60, no. 6, pp. 84–90, 2017.

J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, "You only look once: Unified, real-time object detection," in Proc. IEEE CVPR, Jun. 2016, pp. 779–788.

Md. N. Sakib, "Real-time tiger detection system using YOLOv3," in Proc. IEEE Int. Conf. Comput. Power Commun. Technol. (GUCON), 2021.

S. S. Gaikwad, "Real-time poacher detection using deep learning," in Proc. IEEE Int. Conf. Inventive Syst. Control (ICISC), 2021.

S. Li, "Intelligent wildlife detection using deep neural networks," IEEE Access, vol. 10, pp. 78012–78021, 2022.

R. B. Dave, "Wild animal detection using YOLOv8," in Proc. IEEE Int. Conf. Adv. Comput. Data Sci. (ICACDS), 2023.


Refbacks

  • There are currently no refbacks.