Ai And Machine Learning Techniques For Wildlife Conservation

AI and Machine Learning Techniques for Wildlife Conservation

As the world grapples with the alarming rate of biodiversity loss, the potential of cutting-edge technologies, namely machine learning (ML) and artificial intelligence (AI), revolutionize the way we approach wildlife conservation. From sophisticated sensor technologies to innovative AI algorithms, foundational tools driving this paradigm shift provide a comprehensive understanding of their applications in safeguarding biodiversity. The navigation of systems such as the Spatial Monitoring and Reporting Tool (SMART) and advanced animal detection systems can be used to delve into the intricacies of feature extraction and precise identification. This exploration of predictive modeling, data ethics, citizen science, and the integration of satellite data offers a holistic perspective on the dynamic intersection of technology and conservation. AI and Machine Learning Techniques for Wildlife Conservation illustrates the tangible impact of these technologies on addressing pressing conservation challenges and advocates for the engagement of citizen science initiatives with AI. It fosters a collaborative approach to wildlife conservation that leverages the power of technology for a sustainable future. Covering topics including Internet of Things (IoT), satellite data, and predictive ecosystem management, this book is an excellent resource for conservationists, computer scientists, researchers, professionals, academicians, scholars, and more.

AI and Machine Learning Techniques for Wildlife Conservation

Machine Learning and Internet of Things in Fire Ecology

The destruction of millions of acres of forest land through wildfires is a global cause of concern. Artificial intelligence (AI), transformative in nature, has the potential to transcend and significantly mitigate risk factors of wildfires. AI-driven monitoring systems can detect early signs of wildfire activity, allowing for faster, more targeted responses that can minimize damage and save lives. Machine Learning and Internet of Things in Fire Ecology elucidates and explores the interface of fire ecology with AI, machine learning, and internet of things, as these technologies emerged as a pivotal domain with transformative potential. It will assist environmental-related industries in understanding the paraphernalia and dynamics of the fire ecology ecosystem. Covering topics such as AI, unmanned aerial vehicles (UAVs), and wildlife conservation, this book is an excellent resource for government officials, ecologists, academicians, policymakers, researchers, environmental specialists, industry experts, graduate and postgraduate students, and more.