International Journal of Engineering & Tech Development

E-ISSN: 3067-672X

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Volume 3 Issue 10
October 2026

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Intelligent Engineering Systems for Sustainable Technological Development

Author(s) Shaofan Li
Country United States
Abstract The increasing complexity of technological systems has created a strong need for intelligent engineering approaches that can simultaneously address efficiency, resilience, environmental responsibility, and long-term technological development. Intelligent engineering systems integrate artificial intelligence, machine learning, Internet of Things technologies, digital twins, advanced analytics, automation, and cyber-physical systems to improve engineering decision-making and resource utilization. This paper examines the role of intelligent engineering systems in supporting sustainable technological development across manufacturing, energy, infrastructure, transportation, and other technology-intensive sectors. A conceptual and literature-based methodology is adopted to synthesize major technological capabilities, sustainability contributions, implementation challenges, and future opportunities. The analysis indicates that intelligent systems can improve predictive maintenance, energy optimization, process automation, resource management, operational resilience, and lifecycle performance. AI-based decision-support mechanisms can also facilitate sustainability-oriented engineering decisions by processing large volumes of heterogeneous operational data.
Previous research demonstrates that AI has considerable potential for environmental management, energy efficiency, transportation optimization, water management, and sustainable industrial development. Digital twins further strengthen intelligent engineering by enabling simulation, monitoring, prediction, and optimization of physical assets throughout their operational lifecycles. However, the implementation of intelligent engineering systems is constrained by data quality, interoperability, cybersecurity, computational requirements, organizational capabilities, investment costs, and concerns regarding responsible AI. The paper proposes an integrated perspective in which intelligence and sustainability are treated as interconnected engineering objectives rather than independent technological goals. The findings emphasize that future intelligent engineering systems should incorporate lifecycle sustainability assessment, explainable decision-making, secure data architectures, energy-aware computation, and human-centered system design. Such integration can support the transition from technology-oriented engineering toward adaptive, resilient, and sustainability-oriented technological ecosystems.
Keywords Intelligent Engineering Systems, Sustainable Technology, Artificial Intelligence, Machine Learning, Digital Twins, Cyber-Physical Systems, Smart Engineering, Sustainable Development.
Field Engineering
Published In Volume 2, Issue 3, March 2025
Published On 2025-03-04
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E-ISSN: 3067-672X
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