Overview

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.

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Yogita Yashveer Raghav is an academician and researcher in Computer Science & Engineering. She holds a Ph.D. from Banasthali Vidyapith and serves as an Assistant Professor at K.R. Mangalam University, Gurugram. Her expertise includes Cloud Computing, Edge Computing, Programming Languages, and Web Designing. She is UGC-NET (2020 & 2021) and HTET (2016) qualified and has delivered numerous expert lectures at various colleges and universities. Dr. Raghav has been honored thrice for her contributions in spreading awareness about Science & Technology, Environment, and Cybersecurity among society and the community by Govt. Sr. Sec. School, Bhondsi, Spark Minda Foundation, and Janm Foundation. An active IEEE member, she has published extensively in Scopus-indexed journals and conferences. Surbhi Bhatia Khan is doctorate in Computer Science and Engineering in machine learning and social media analytics. She is listed in the top 2% researchers released by the Stanford University, USA. She earned Project management Professional Certification from reputed Project Management Institute, USA. She is currently working in the Department of Data Science, School of Science, Engineering and environment, University of Salford, Manchester, United Kingdom. She holds research positions Lebanese American University. She also enjoys adjunct professor position from Shoolini University, Himachal Pradesh, India. She has more than 12 years of academic and teaching experience in different universities. She has published 100+ papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia and USA. She has successfully authored and edited 12 books. She has completed research funded projects from Deanship of Scientific Research, Ministry of Education from Saudi Arabia, and India. She is working in the research projects with UKRI, EU, and RDIA and also with King Salman Disability research programme. She is a senior member of IEEE, a member of IEEE Young Professionals, and ACM. She has chaired several international conferences and workshops and has delivered over 20 invited and keynote talks across the globe. She is serving as an Academic editor, Associate Editor and Guest editor in many reputed journals including Springer, Tech science press, Bentham Science, PLOS ONE journals, MDPI and HCIS. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia in 2021. Her area of interests are Information Systems, Sentiment Analysis, Machine Learning, Databases, and Data Science.

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