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Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India

Shivaprakash, Kadukothanahally Nagaraju ; Swami, Niraj ; Mysorekar, Sagar ; Arora, Roshni ; Gangadharan, Aditya ; Vohra, Karishma ; Jadeyegowda, Madegowda ; Kiesecker, Joseph M.

Sustainability, 2022-06, Vol.14 (12), p.7154 [Periódico revisado por pares]

Basel: MDPI AG

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Título:
Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India
Autor: Shivaprakash, Kadukothanahally Nagaraju ; Swami, Niraj ; Mysorekar, Sagar ; Arora, Roshni ; Gangadharan, Aditya ; Vohra, Karishma ; Jadeyegowda, Madegowda ; Kiesecker, Joseph M.
Assuntos: Agriculture ; Artificial intelligence ; Automation ; Biodiversity ; Carbon ; Conservation ; Data collection ; Data science ; Deforestation ; Developing countries ; Drones ; Forest conservation ; Forest management ; Forest resources ; Forestry ; Forests ; Hydrology ; Innovations ; Internet of Things ; Inventory ; LDCs ; Learning algorithms ; Machine learning ; New technology ; Nonprofit organizations ; Satellite technology ; Social networks ; Sustainability ; Technology ; Technology adoption ; Timber ; Urban agriculture ; Urban areas ; Wildlife ; Wildlife conservation
É parte de: Sustainability, 2022-06, Vol.14 (12), p.7154
Descrição: The recent advancement in data science coupled with the revolution in digital and satellite technology has improved the potential for artificial intelligence (AI) applications in the forestry and wildlife sectors. India shares 7% of global forest cover and is the 8th most biodiverse region in the world. However, rapid expansion of developmental projects, agriculture, and urban areas threaten the country’s rich biodiversity. Therefore, the adoption of new technologies like AI in Indian forests and biodiversity sectors can help in effective monitoring, management, and conservation of biodiversity and forest resources. We conducted a systematic search of literature related to the application of artificial intelligence (AI) and machine learning algorithms (ML) in the forestry sector and biodiversity conservation across globe and in India (using ISI Web of Science and Google Scholar). Additionally, we also collected data on AI-based startups and non-profits in forest and wildlife sectors to understand the growth and adoption of AI technology in biodiversity conservation, forest management, and related services. Here, we first provide a global overview of AI research and application in forestry and biodiversity conservation. Next, we discuss adoption challenges of AI technologies in the Indian forestry and biodiversity sectors. Overall, we find that adoption of AI technology in Indian forestry and biodiversity sectors has been slow compared to developed, and to other developing countries. However, improving access to big data related to forest and biodiversity, cloud computing, and digital and satellite technology can help improve adoption of AI technology in India. We hope that this synthesis will motivate forest officials, scientists, and conservationists in India to explore AI technology for biodiversity conservation and forest management.
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Idioma: Inglês

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Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India

Shivaprakash, Kadukothanahally Nagaraju ; Swami, Niraj ; Mysorekar, Sagar ; Arora, Roshni ; Gangadharan, Aditya ; Vohra, Karishma ; Jadeyegowda, Madegowda ; Kiesecker, Joseph M.

Basel: MDPI AG

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