From sensing to semantics: a comprehensive survey of AI-based animal behavior monitoring via pose estimation, behavior recognition, and UAV-enabled observation
This comprehensive review on animal behavior intelligent monitoring aims to systematically summarize the latest advanced technological frontiers of advanced artificial intelligence in animal behavior monitoring, also to identify the research challenges and explore future research directions in this field.
This study presents a low-cost, open-source system designed for non-invasive monitoring of budgerigars, a small parrot species frequently used in animal behavior research, offering valuable insights for research and husbandry while prioritizing animal welfare.
Highlights
Systematic mapping study on insect monitoring with computer vision.
Review of 114 relevant research studies.
State-of-the-art of multi-object detection and tracking applied to insect monitoring.
Challenges and possible solutions for insect monitoring.
Abstract.
Ins...
R. R. V. Leocádio, A. Segundo, Eduardo José da S. Luz et al.· Applied Engineering in Agric...· 0 citations
This work proposes the first artificial intelligence-based, real-time, non-contact framework for automatic behavior detection and tracking of Mithun in natural farm environments, which offers significant potential for improving reproductive management, enhancing animal welfare, and enabling continuous precision livesto...
J. A. Valan, Prokash Gogoi, Sanjana Gupta et al.· Engineering Research Express· 0 citations
Wildlife and human activities are key components of ecological systems, and understanding their spatiotemporal patterns is essential for evaluating human–wildlife interactions and informing conservation planning. Camera trap networks function as terrestrial remote sensing systems that enable continuous monitoring of ec...
Hao Chen, Fang Qiu, Umme Kulsum et al.· Zeitschrift f\ ur Jagdwissen...· 0 citations
This article presents a systematic literature review of wildfire monitoring approaches using satellite and aerial remote sensing, fixed cameras, wireless sensor networks, and Internet of Things (IoT) platforms combined with machine learning (ML) and deep learning (DL) models for ignition detection, fire-weather indices...
Saba Mustafa, Mahsa Mohaghegh, Iman Ardekani et al.· Italian National Conference...· 0 citations
Experiments show that the proposed framework achieves accurate behavioral state recognition and reliable state-transition prediction, while remaining robust under interference and real-world conditions and maintaining real-time processing suitable for resource-constrained deployment.
Runze Mao, Teng Wu, Sheng-Jun Wei et al.· Drones· 0 citations
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