Abstract Advanced technologies are experiencing significant transformation through AI (Artificial Intelligence), where mathematical foundations serve as the backbone of classical and modern AI models. Despite rapid advancements and widespread adoption, there is a lack of a unified framework for core AI components, comprising building blocks, governing equations, parameters, evaluation criteria, benchmarks, performance metrics, and objective functions across technological domains. In this comprehensive survey, we address this gap in the areas of energy, renewable energy and water, smart buildings and cities, the environment and climate change, hydrogen and hydrogen fuel cells, and cross-sector advanced technologies, including robotics and autonomous systems, computer vision, finance, and industrial manufacturing, with systematic intercomparison and benchmarking. In addition, we conduct a taxonomy-based analysis with a methodological focus on AI models, their underlying parameters and governing equations, as well as their pros, cons, trade-offs, comparative analyses, and directions for future development. This survey consolidates these elements into a structured reference that defines key requirements for AI development in high-tech sectors and provides a forward-looking roadmap to foster innovation beyond current technological infrastructures.
Amini et al. (Sat,) studied this question.