Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective. - Uncovering extended functions of AI in Microbiology. - Production and development of novel drug targets through AI. - Challenges for using and selecting appropriate AI tools in health, agriculture and food sector

This textbook addresses global and local environmental problems and the involvement of microorganisms in their development and remediation. In particular, methodological aspects, some of them molecular genetic, for the study of microbial communities are considered. Overall, the prominent role of microorganisms in various material cycles is presented. In addition to biochemical principles for the degradation of environmental pollutants, the use of microorganisms in environmental biotechnological processes for the purification of air, water or soil as well as in environmentally friendly production processes is discussed. The book is intended for biologists with an interest in environmental microbiological issues, but also for students of process or environmental engineering, geoecology or geology, as well as students of other environmental science disciplines. For the 3rd edition, the authors have completely revised, corrected, updated and supplemented the book.

Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective.

This book offers information on intelligent and computational techniques for microbial data associated with plant microbes, human microbes etc. The main focus of this book is to provide an insight on building smart sustainable solutions for microbial technology using intelligent computational techniques. Microbes are ubiquitous in nature, and their interactions among each other are important for colonizing diverse habitats. The core idea of sustainable computing is to deploy algorithms, models, policies and protocols to improve energy efficiency and management of resources, enhancing ecological balance, biological sustenance and other services on societal contexts. Chapters in this book explore the conventional methods as well as the most recently recognized high-throughput technologies which are important for productive agroecosystems to feed the growing global population. This book is of interest to teachers, researchers, microbiologist, computer bioinformatics scientists, plant and environmental scientist, and those interested in environment stewardship around the world. The book also serves as an advanced textbook material for undergraduate and graduate students of computer science, biomedicine, agriculture, human science, forestry, ecology, soil science, and environmental sciences and policy makers.

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. - Presents tools, connections and proactive solutions to take sustainability programs to the next level - Offers a practical guide for making students proficient in modern electronic data analysis and graphics - Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery