Different fields of Artificial Intelligence (AI) such as machine learning, image processing and neural network have an increasing range of applications in both macro and micro scales. Microbiology is a field experiencing a revolution in methodology after the development of AI. Machine learning, image processing, pattern recognition and other subcategories of AI have found their places in microbiological analyses and measurement during recent years. Environmental microbiology is a crucial area across many fields: ecology, environmental science and engineering, in which continuous monitoring of the microorganisms and optimization of their growth is of high importance. In order to achieve this goal, AI-based methods and algorithms have been introduced to environmental microbiology due to their accuracy, efficiency and simplicity, and have shown noticeable potential for being developed further and commercialized. Therefore, a great deal of research works have been focusing on developing AI application in environmental microbiology.
The digital revolution of the 21st century has changed our approach to fundamental concepts such as measurement, analysis, monitoring and design in all areas, especially microbiology, and non-invasive direct approaches based on AI have replaced the conventional methodologies in these areas. These approaches have significantly facilitated the connections between different analytical devices and systems, which not only increases the reliability and comprehensiveness of analyzing, but also enhances the flexibility in microbiological system design (e.g. biological treatment systems, microbial cultivations, biotoxic prevention, etc.) which results in higher productivity. This Research Topic will be a useful database for collecting scientific information on AI application in environmental microbiology. Our main objective is to provide a platform for recent upgrades of the methodologies and analyses in the field of environmental microbiology using the potentials of AI. We aim to provide a comprehensive overview of this multidisciplinary field from different perspectives, as well as a broader context for assessing the possibilities for commercialization in the form of microbiological softwares, devices, sensors and methods.
This Research Topic will include Original Research papers, critical Reviews focusing on recent achievements in this field and short Perspectives. Papers in a wide range of disciplines including biology, environmental science and engineering, chemistry and chemical engineering, computers and electronics, and bioelectrics, addressing the subthemes from below with a clear focus on environmental microbiology are welcomed:
- Developing AI-based methods and analyses
- Microbial process optimization by AI algorithms
- Sensors fabrication
- Internet of things (IOT)
- Process system engineering and integration
- Bioinformatics
- New software, codes, algorithms and devices
- Modeling, numerical analysis and simulation
- Cyberinfrastructure, informatics and intelligent systems
Different fields of Artificial Intelligence (AI) such as machine learning, image processing and neural network have an increasing range of applications in both macro and micro scales. Microbiology is a field experiencing a revolution in methodology after the development of AI. Machine learning, image processing, pattern recognition and other subcategories of AI have found their places in microbiological analyses and measurement during recent years. Environmental microbiology is a crucial area across many fields: ecology, environmental science and engineering, in which continuous monitoring of the microorganisms and optimization of their growth is of high importance. In order to achieve this goal, AI-based methods and algorithms have been introduced to environmental microbiology due to their accuracy, efficiency and simplicity, and have shown noticeable potential for being developed further and commercialized. Therefore, a great deal of research works have been focusing on developing AI application in environmental microbiology.
The digital revolution of the 21st century has changed our approach to fundamental concepts such as measurement, analysis, monitoring and design in all areas, especially microbiology, and non-invasive direct approaches based on AI have replaced the conventional methodologies in these areas. These approaches have significantly facilitated the connections between different analytical devices and systems, which not only increases the reliability and comprehensiveness of analyzing, but also enhances the flexibility in microbiological system design (e.g. biological treatment systems, microbial cultivations, biotoxic prevention, etc.) which results in higher productivity. This Research Topic will be a useful database for collecting scientific information on AI application in environmental microbiology. Our main objective is to provide a platform for recent upgrades of the methodologies and analyses in the field of environmental microbiology using the potentials of AI. We aim to provide a comprehensive overview of this multidisciplinary field from different perspectives, as well as a broader context for assessing the possibilities for commercialization in the form of microbiological softwares, devices, sensors and methods.
This Research Topic will include Original Research papers, critical Reviews focusing on recent achievements in this field and short Perspectives. Papers in a wide range of disciplines including biology, environmental science and engineering, chemistry and chemical engineering, computers and electronics, and bioelectrics, addressing the subthemes from below with a clear focus on environmental microbiology are welcomed:
- Developing AI-based methods and analyses
- Microbial process optimization by AI algorithms
- Sensors fabrication
- Internet of things (IOT)
- Process system engineering and integration
- Bioinformatics
- New software, codes, algorithms and devices
- Modeling, numerical analysis and simulation
- Cyberinfrastructure, informatics and intelligent systems
