6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions
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Vivek Pandya
Abstract
The chapter explores the integration of artificial intelligence (AI) in environmental microbiology, highlighting its transformative impact on managing and comprehending microbial ecosystems. It offers insights into the historical progression of AI within this field, emphasizing the pivotal roles of machine learning and deep learning. The discussion extends to their applications in microbial ecology, metagenomics, and environmental monitoring. Furthermore, the chapter delves into the evolving applications of AI in areas such as bioremediation, climate change studies, and marine ecosystems. It also addresses key challenges, including data quality, ethical considerations, and technical limitations, in a simplified manner. Overall, this chapter underscores AI’s potential to revolutionize our understanding and management of microbial life across diverse environments.
Abstract
The chapter explores the integration of artificial intelligence (AI) in environmental microbiology, highlighting its transformative impact on managing and comprehending microbial ecosystems. It offers insights into the historical progression of AI within this field, emphasizing the pivotal roles of machine learning and deep learning. The discussion extends to their applications in microbial ecology, metagenomics, and environmental monitoring. Furthermore, the chapter delves into the evolving applications of AI in areas such as bioremediation, climate change studies, and marine ecosystems. It also addresses key challenges, including data quality, ethical considerations, and technical limitations, in a simplified manner. Overall, this chapter underscores AI’s potential to revolutionize our understanding and management of microbial life across diverse environments.
Chapters in this book
- Frontmatter I
- Dedication V
- Preface VII
- Contents IX
- 1 Understanding artificial intelligence: an introduction, history, and foundations 1
- 2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI 25
- 3 Cellular image classification and identification of genetic variations using artificial intelligence 47
- 4 Artificial intelligence in bacterial staining and cell counting 65
- 5 Use of artificial intelligence in the prediction of microbial species 79
- 6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions 97
- 7 AI in food production and processing: applications and challenges 125
- 8 Artificial intelligence in microbial food safety 153
- 9 AI in plant growth promotion and plant disease management 183
- 10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology 207
- 11 Artificial intelligence in diagnostics 229
- 12 Artificial intelligence in bacterial culture plate images 263
- 13 Prediction of antimicrobial activity using artificial intelligence 281
- 14 Artificial intelligence and MALDI-TOF MS 313
- 15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare 337
- 16 Reimagining perfusion bioreactors with artificial intelligence 357
- Index 381
Chapters in this book
- Frontmatter I
- Dedication V
- Preface VII
- Contents IX
- 1 Understanding artificial intelligence: an introduction, history, and foundations 1
- 2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI 25
- 3 Cellular image classification and identification of genetic variations using artificial intelligence 47
- 4 Artificial intelligence in bacterial staining and cell counting 65
- 5 Use of artificial intelligence in the prediction of microbial species 79
- 6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions 97
- 7 AI in food production and processing: applications and challenges 125
- 8 Artificial intelligence in microbial food safety 153
- 9 AI in plant growth promotion and plant disease management 183
- 10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology 207
- 11 Artificial intelligence in diagnostics 229
- 12 Artificial intelligence in bacterial culture plate images 263
- 13 Prediction of antimicrobial activity using artificial intelligence 281
- 14 Artificial intelligence and MALDI-TOF MS 313
- 15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare 337
- 16 Reimagining perfusion bioreactors with artificial intelligence 357
- Index 381
