This book explores the convergence of microbiology and artificial intelligence (AI) and delves into the intricate world of microbial systems enhanced by cutting-edge AI technologies. The book begins by establishing a foundation in the fundamentals of microbial ecosystems and AI principles. It elucidates the integration of AI in microbial genomics, demonstrating how advanced algorithms analyze genomic data and contribute to genetic engineering. Bioinformatics and computational microbiology are explored, showcasing AI's role in predictive modeling and computational tools. The intersection of AI and microbial applications extends to drug discovery, precision agriculture, and pathogen detection. Readers gain insights into AI-driven drug development, the optimization of agricultural practices using microbial biostimulants, and early warning systems for crop diseases. The book highlights AI's role in microbial biotechnology, elucidating its impact on bioprocessing, fermentation, and other biotechnological applications. Climate-smart agriculture and microbial adaptations to environmental challenges are discussed, emphasizing sustainable practices.

This book caters to a diverse audience including teachers, researchers, microbiologist, computer bioinformaticians, plant and environmental scientists. The book serves as additional reading material for undergraduate and graduate students of computer science, biomedical, agriculture, human science, forestry, ecology, soil science, and environmental sciences and policy makers to be a useful to read.

Provides an interdisciplinary exploration of the symbiotic potential between microbiology and artificial intelligence Discusses cutting-edge applications from ecological modeling to biotechnological advancements in microbiology Examines and addresses the responsible use of artificial intelligence in microbial research

Autorentext

Dr. Babita Pandey obtained her PhD degree in computer engineering from IIT Varanasi, India. She serves as an academician and a researcher for the past ten years. She is currently an Associate Professor in Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India. She has published more than 100 scientific research publications in reputed international and national journals and conferences, which are indexed in various international databases. Her research areas include medical informatics, soft computing, educational technologies, expert systems, and data mining.

Dr. Devendra Kumar Pandey is currently working as Professor at Lovely Professional University, India. He obtained his PhD in biochemical engineering from IIT-BHU, Varanasi, India. His research interests are pharmacology and toxicology, plant and soil sciences, and molecular sciences. His area of expertise includes plant biotechnology, plant-microbe interaction, chromatography techniques, molecular markers and bioactive compounds markers for medicinal plants. He has published 89+ articles in international journals, and 40+ articles in national and international conferences where he contributed as an author/co-author.

Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research & development of 9 years. He is currently working as an Assistant Professor and coordinator of Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his PhD degree from Lovely Professional University, Punjab in May 2018. He has completed his M.Tech. from VIT University and B. Tech. from RGPV, Bhopal. He has completed his PDF from UNIFOR, Brazil. He has 95+ research papers along with book chapters including more than 15 papers in SCI-indexed journals with cumulative impact factor of above 50 to his credit. His research interest includes machine learning, deep learning, educational technologies and computer vision.

Dr. Venkatesh Dutta has contributed to significant changes in public discourse, law and policy for sustainable water resource management in India. He has been a Fulbright Scholar, USA and a British Chevening Fellow, UK. He has done his PhD from TERI and post-doctoral research at the University of Maryland, USA. He is a member of the smaller river rejuvenation committee of Uttar Pradesh and currently working on restoration of rivers and smaller streams of Gomti, Ghaghra and Rapti basins. His research interests span water resource management with particular emphasis on catchment planning, river restoration and eco-hydrology. Dr. Venkatesh served as a member in the drafting committee of State Water Policy 2020 of Uttar Pradesh. He is a member of the District Environment Committee and District Ganga Committee and has contributed to drafting of STI Policy Framework 2020 of the Department of Science and Technology, Govt. of India. He has guided nine doctoral students and contributed to more than 100 scholarly papers and chapters in journals and books of international repute. He is a Fellow of Indian Water Resources Society (IWRS), IIT, Roorkee and Society of Earth Sciences (SES), India.

Dr. Valentina E. Balas is currently a Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, "Aurel Vlaicu" University of Arad, Romania. She holds a PhD Cum Laude in applied electronics and telecommunications from Polytechnic University of Timisoara. Dr. Balas has authored more than 400 research papers in refereed journals and international conferences. Her research interests are in intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling and simulation. Dr. Balas is the Director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad and ****Director of

Inhalt

Chapter 1. Thematic Analysis of Media Influence on the Adoption of AI Climate Prediction Models in Microbial Agriculture Practices: A Case Study of Uttar Pradesh Using Diffusion of Innovations Theory.- Chapter 2. Understanding Media Influence on the Adoption of AI Climate Prediction Models in Microbiological Agricultural Practices: A Study of Uttarakhand.- Chapter 3. Advancements in Precision Agriculture: Integrating Machine Learning Techniques for Crop Monitoring and Management.- Chapter 4. Advances in Agricultural Analytics Machine Learning Applications for Crop Monitoring and Management.- Chapter 5. AI Driven Strategies for Microbial Infection from Discovery to Therapeutic Design.- Chapter 6. Use of Artificial Intelligence for Monitoring Algal Blooms in Aquatic Ecosystem.- Chapter 7. Ai-Yolact Model for Automatic Severity Grading Of Microbial Based Anthracnose Infection in Camellia Leaves.- Chapter 8. An Explainable AI Based CNN model for Plant Disease Diagnosis.- Chapter 9. Artificial Intelligent Enable Intelligent Bio-Sensor for Microbial Analysisfor Lung Health.- Chapter 10. Biosensors Guided Ai Interventions in Personalized Medicines.- Chapter 11. Education and Training for Developing Responsible AI Solutions in Healthcare.- Chapter 12. Automation of Drug Discovery & Development.- Chapter 13. Genome Studies and Disease Diagnosis.- Chapter 14. Exploring Explainable Artificial Intelligence in Healthcare: Issues, Challenges and Opportunities.- Chapter 15. Investigating Integron as the Principal Factor of Antibiotic Resistance in the Human Gut: A Holistic Perspective.- Chapter 16. Hybrid Deep Learning for Predictive Modelling of Microbial Biostimulants in Precision Agriculture.- Chapter 17. Challenges and Opportunities In Integrating Generative Al With Wearable Devices.- Chapter 18. Medical Image Analysis and Morphology Using Artificial Intelligence.- Chapter 19. Simulation of Biological Structures Using Generative Artificial Intelligence.- Chapter 20. Neuromuscular Disease Classification: Leveraging Deep Learning Feature Extractors and Applications.