1N. Vasireddi, 1R.O. Azizov, 2J.S. Rakhmatov
Annotation:
This article systematizes the role of artificial intelligence (AI), the Internet of Things (IoT), blockchain technologies, digital twins, and remote sensing systems in environmental monitoring and the energy transition. A comprehensive analysis is conducted of current digital solutions applied to environmental condition tracking, renewable energy source (RES) management, and energy infrastructure optimization under conditions of growing climate instability. It is shown that the implementation of digital technologies ensures RES generation forecasting with an accuracy of 90–95%, reduces equipment downtime by 20%, decreases fault diagnosis time by 87.5%, lowers operating costs by 11%, and improves the accuracy of carbon reporting by 25%, thereby collectively enhancing the effectiveness of managerial decision-making. Alongside these positive effects, significant barriers constraining the large-scale adoption of such solutions have been identified: environmental costs associated with equipment manufacturing, operation, and disposal; growing cyber risks arising from the increasing complexity of digital infrastructure; high initial investment requirements; and digital inequality between regions and countries, which limits equitable access to technology. Based on the analysis conducted, the necessity of forming a sustainable synergy between digital technologies and environmental responsibility principles is substantiated as a key condition for achieving global sustainable development climate goals by 2030.
Keywords: digital technologies, artificial intelligence, Internet of Things, blockchain, digital twins, renewable energy, environmental monitoring.