Published: Dec. 7, 2024
Language: Английский
Conservation, Journal Year: 2024, Volume and Issue: 4(4), P. 685 - 702
Published: Nov. 11, 2024
The rapid decline in global biodiversity demands innovative conservation strategies. This paper examines the use of artificial intelligence (AI) wildlife conservation, focusing on Conservation AI platform. Leveraging machine learning and computer vision, detects classifies animals, humans, poaching-related objects using visual spectrum thermal infrared cameras. platform processes these data with convolutional neural networks (CNNs) transformer architectures to monitor species, including those that are critically endangered. Real-time detection provides immediate responses required for time-critical situations (e.g., poaching), while non-real-time analysis supports long-term monitoring habitat health assessment. Case studies from Europe, North America, Africa, Southeast Asia highlight platform’s success species identification, monitoring, poaching prevention. also discusses challenges related quality, model accuracy, logistical constraints outlining future directions involving technological advancements, expansion into new geographical regions, deeper collaboration local communities policymakers. represents a significant step forward addressing urgent offering scalable adaptable solution can be implemented globally.
Language: Английский
Citations
4
Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 97 - 132
Published: Jan. 10, 2025
Artificial Intelligence (AI) has become a transformative tool in wildlife conservation, enabling advanced data analysis, species monitoring, and habitat management. However, its application faces significant challenges. This chapter examines the technical, ethical, practical obstacles associated with AI conservation. Technically, AI's success depends on quality quantity of available data, biases collection can result flawed models predictions. Ethically, concerns arise over use surveillance technologies that could infringe rights indigenous communities, broader implications AI-driven decisions biodiversity Additionally, challenges such as inadequate infrastructure remote areas, limited funding, need for greater interdisciplinary collaboration are explored. Through critical aims to provide balanced perspective role advocating thoughtful innovative approach maximize potential while addressing limitations.
Language: Английский
Citations
0
Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 19 - 48
Published: Jan. 10, 2025
The integration of artificial intelligence (AI) into wildlife conservation has revolutionized methodologies for monitoring species, enhancing habitat management, and combating poaching. This chapter examines various AI applications that contribute to the protection preservation biodiversity. Remote sensing technologies, powered by machine learning algorithms, assist in assessing health tracking changes over time. AI-driven image recognition tools enable identification individual animals from camera trap photos, facilitating more accurate population estimates behavioral studies. Moreover, predictive analytics play a crucial role forecasting human-wildlife conflicts informing proactive management strategies. synthesis technologies demonstrates their potential enhance efforts, optimize resource allocation, ultimately foster effective initiatives. ongoing advancement this field promises create innovative solutions some most pressing challenges.
Language: Английский
Citations
0
Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103120 - 103120
Published: March 1, 2025
Language: Английский
Citations
0
Biodiversity, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 2
Published: Oct. 30, 2024
Language: Английский
Citations
0
Global Ecology and Conservation, Journal Year: 2024, Volume and Issue: 54, P. e03109 - e03109
Published: July 23, 2024
Domestic dogs, Canis familiaris, wandering into natural habitats poses a grave threat to wildlife, increasing predation pressure and disease risk disrupting the ecological balance within ecosystems. This study examines presence of dogs in European Protected Area (PA), Doñana National Park (SW Spain), where their access is strictly restricted, explores how dog relates potential points. We utilised classifications provided by citizen science artificial intelligence, subsequently validated experts, detect 5200,000 photos taken 60 camera traps randomly deployed across PA from October 2020 January 2024. discovered 33 primarily groups 2–5 individuals, recorded 31 detection events at 22 locations. Dogs were detected ranging 10 42 km2 (Minimum Convex Polygon) PA. The probability increased 0.22 log odds per kilometre closer village (corresponding an increase 0.5 approximately 0.55) bordering exceeded 0.9 near it. Our data revealed three types PA: accompanying poachers, free-roaming living nearby human settlements, stray most likely relying on resources. Urgent actions are needed as pose severe threats endangered species like Iberian lynx Lynx pardinus (six adult female documented killed dogs). recommend raising awareness among local authorities particularly settlements close PAs, should be banned. Regularly monitoring PAs crucial prevent invasions associated impacts. findings underscore importance using integrating intelligence with monitor invasive effectively.
Language: Английский
Citations
0
Published: Dec. 7, 2024
Language: Английский
Citations
0