Biodiversity Conservation, Internet of Things in Environmental Science, Deep Learning-Reference-Cited by-同舟云学术

Biodiversity Conservation, Internet of Things in Environmental Science, Deep Learning

Published:2024-06-07 Issue: Volume: Page:137-159
ISSN:2326-9162
Container-title:Advances in Environmental Engineering and Green Technologies
language:
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Author:

Sharma Manoj Kumar¹,Poonguzhali M.²,Sandepogu Prashanthi³,Logeswaran S.⁴,Das Abhijeet⁵^ORCID,Myilsamy Sureshkumar⁶

Affiliation:

1. Department of Botany, Neeraj Memorial College, India

2. Department of Electronics and Communication Engineering, R.P. Sarathy Institute of Technology, India

3. Department of Botany, TSWRDC (W), India

4. Department of Civil Engineering, KPR Institute of Engineering and Technology, India

5. Department of Civil Engineering, C.V. Raman Global University, India

6. Bannari Amman Institute of Technology, India

Abstract

Biodiversity conservation is crucial in addressing environmental degradation and climate change. The integration of IoT technologies and deep learning can revolutionize environmental science and conservation efforts. The chapter discusses the foundational concepts of biodiversity conservation, IoT's fundamentals, and deep learning's role in analyzing vast datasets. IoT devices collect data at various scales, while deep learning algorithms analyze this data to identify patterns and predict ecological trends. The chapter also addresses ethical considerations, challenges, and future directions in using digital technologies for biodiversity conservation, emphasizing the importance of interdisciplinary collaboration and technological innovation in safeguarding Earth's biodiversity for future generations.

Publisher

IGI Global

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