Editorial: Artificial Intelligence in Environmental Microbiology

Perhaps twenty-first century is so called “Digital Era” since digitalization and artificial intelligence (AI) is finding its way into every aspect of human life. Nowadays, AI-based approaches are gaining a lot of traction as components of research and development in different scientific and technological fields. One of the areas that is experiencing a digital revolution is environmental microbiology, which is the science of studying the interactions between the microorganisms and the environment and their mutual impacts (Pepper et al., 2011). Approaches such as machine learning (ML), deep learning (DL), image processing, pattern recognition and internet of things (IoT) are being widely implemented in this field in all aspects from theoretical development and identification to process monitoring and optimization (Asgharnejad and Sarrafzadeh, 2020; Gargalo et al., 2020; Asgharnejad et al., 2021). Outbreak of the global challenge of COVID-19 pandemic during the last 2 years and the huge impacts of this virus on socioeconomic infrastructures has also highlighted the necessity of innovative approaches for controlling and monitoring microbial communities in the environment. This special issue provides a platform for gathering the most recent advances in the fields of environmental microbiology from the perspective of AI. It includes 10 scientific papers (six original research articles, two mini-reviews and two reviews) that cover a wide range of AI approaches including ML, DL, and image processing. Two of these papers are specifically focused on using AI for diagnosis and tackling the SARS-CoV-2 virus, which is the species causing COVID-19 and, in this regard, the current Research Topic can be a reference for ongoing research on the edge of science to overcome the pandemic and prevent future such catastrophic outbursts.