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Volume 24
Issue 11
10.3390/s24113409
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Article

A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices

by
Dmitrij Teterja
1,*,
Jose Garcia-Rodriguez
1,*,
Jorge Azorin-Lopez
1,
Esther Sebastian-Gonzalez
2,
Daliborka Nedić
3,
Dalibor Leković
3,
Petar Knežević
3,
Dejan Drajić
3,4 and
Dejan Vukobratović
5
1
Department of Computer Science and Technology, University of Alicante, 03690 San Vicente del Raspeig, Alicante, Spain
2
Department of Ecology, University of Alicante, 03690 San Vicente del Raspeig, Alicante, Spain
3
DunavNet DOO, Bulevar Oslobođenja 133/2, 21000 Novi Sad, Serbia
4
Paviljon Računskog Centra, The Department of Telecommunications, School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11120 Belgrade, Serbia
5
Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia
*
Authors to whom correspondence should be addressed.
Sensors 2024, 24(11), 3409; https://doi.org/10.3390/s24113409
Submission received: 2 May 2024 / Revised: 22 May 2024 / Accepted: 24 May 2024 / Published: 25 May 2024
(This article belongs to the Section Sensing and Imaging)
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Abstract

Chicken behavior recognition is crucial for a number of reasons, including promoting animal welfare, ensuring the early detection of health issues, optimizing farm management practices, and contributing to more sustainable and ethical poultry farming. In this paper, we introduce a technique for recognizing chicken behavior on edge computing devices based on video sensing mosaicing. Our method combines video sensing mosaicing with deep learning to accurately identify specific chicken behaviors from videos. It attains remarkable accuracy, achieving 79.61% with MobileNetV2 for chickens demonstrating three types of behavior. These findings underscore the efficacy and promise of our approach in chicken behavior recognition on edge computing devices, making it adaptable for diverse applications. The ongoing exploration and identification of various behavioral patterns will contribute to a more comprehensive understanding of chicken behavior, enhancing the scope and accuracy of behavior analysis within diverse contexts.
Keywords: chicken behavior recognition; convolution neural networks; mosaic images; mosaic videos; edge computing chicken behavior recognition; convolution neural networks; mosaic images; mosaic videos; edge computing

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MDPI and ACS Style

Teterja, D.; Garcia-Rodriguez, J.; Azorin-Lopez, J.; Sebastian-Gonzalez, E.; Nedić, D.; Leković, D.; Knežević, P.; Drajić, D.; Vukobratović, D. A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices. Sensors 2024, 24, 3409. https://doi.org/10.3390/s24113409

AMA Style

Teterja D, Garcia-Rodriguez J, Azorin-Lopez J, Sebastian-Gonzalez E, Nedić D, Leković D, Knežević P, Drajić D, Vukobratović D. A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices. Sensors. 2024; 24(11):3409. https://doi.org/10.3390/s24113409

Chicago/Turabian Style

Teterja, Dmitrij, Jose Garcia-Rodriguez, Jorge Azorin-Lopez, Esther Sebastian-Gonzalez, Daliborka Nedić, Dalibor Leković, Petar Knežević, Dejan Drajić, and Dejan Vukobratović. 2024. "A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices" Sensors 24, no. 11: 3409. https://doi.org/10.3390/s24113409

APA Style

Teterja, D., Garcia-Rodriguez, J., Azorin-Lopez, J., Sebastian-Gonzalez, E., Nedić, D., Leković, D., Knežević, P., Drajić, D., & Vukobratović, D. (2024). A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices. Sensors, 24(11), 3409. https://doi.org/10.3390/s24113409

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