Water and electricity consumption management architectures using IoT and AI: A review study

Abstract

Abstract. This in-depth article delves into the implemented architectures aimed at optimizing water and electricity consumption through the integration of the Internet of Things (IoT) and artificial intelligence (AI). It provides a detailed analysis of various developments, trends, and key technologies shaping this rapidly evolving field. The article meticulously examines background research and scrutinizes the architecture, thus offering profound insights into the technical challenges, potential benefits, and implementation obstacles of leveraging IoT and AI in resource management. By exploring these architectures, the article highlights significant advancements in terms of efficiency, resource utilization, and predictive capabilities within integrated systems. Convincing results demonstrate the positive impact of this technological convergence on environmental sustainability, waste reduction, and resource optimization, thus offering a promising vision for the future of resource management. Furthermore, an extensive discussion section critically evaluates the discussed approaches, pinpointing the strengths and weaknesses of each method and proposing avenues for improvement and development. This nuanced analysis provides a solid foundation for future research and continuous innovation in the field of resource management. This article serves as an essential resource for professionals and researchers working in the fields of water, energy, and IoT/AI. It offers an in-depth understanding of the challenges and opportunities associated with integrating these technologies and provides strategic guidance for effective and sustainable resource management in the digital age.