A comprehensive review of frugal artificial intelligence: challenges, applications, and the road to sustainable AI

Artificial Intelligence (AI) has demonstrated its transformative impact in creating learning models, processing extensive datasets, and executing intricate calculations rapidly. Nevertheless, achieving optimal performance with AI models demands substantial investment in powerful and expensive high-end hardware. The learning models running on the hardware are complex, requiring massive data and huge training time. However, the race to achieve higher accuracy and computational limitations of AI further poses a threat to the environment and thus provides motivation to develop AI technology that is cost-effective, scalable, and suitable for resource-constrained environments, Frugal Artificial Intelligence, or Frugal AI. The objective of this paper is to present a detailed survey of the latest concepts and applications of Frugal AI. The definition, concept, history, and evolution of Frugal AI are discussed in the paper. The article presents the key characteristics of Frugal AI, as well as the ethical considerations and techniques needed for developing Frugal AI systems. Further, the challenges in Frugal AI are discussed along with potential future research directions. The paper concludes by highlighting the role of Frugal AI in Industry 4.0. This paper provides a comprehensive overview of Frugal AI and will help researchers, practitioners, and policymakers to better understand the technology and aim for sustainable and green computation.