A Critical Review of Intelligent Engineering Systems for Sustainable Technological Advancement

Abstract

The fast development of intelligent systems of engineering has become one of the facilitators of sustainable technological progress in a variety of application fields. These systems capitalize on the combination of artificial intelligence (AI), Internet of Things (IoT), edge computing and further optimization methods to elevate the efficiency of operations, cut down on energy use, and assist environmentally friendly solutions. This paper critically covers intelligent engineering systems, their architectural paradigms, enabling technologies, and their application in intelligent agriculture, energy systems, healthcare and in intelligent cities. An analytic framework is followed to analyze the existing approaches in terms of the key performance measures, such as energy efficiency, latency, scalability, reliability and complexity of computation. The review also offers a comparative evaluation of edge-cloud hybrid architecture and AI-driven optimization strategies, the strengths, and limitations of the architectures in real-world deployments. The most important challenges including data security, interoperability, resource limitations and real-time processing demands are critically discussed. Lastly, the paper also identifies future research opportunities, such as the necessity of green AI models, federated learning systems, and standardized assessment systems. This review has important implications to researchers and practitioners seeking to develop the next-generation intelligent systems to ensure a sustainable technological development.