Intelligent Construction Ecosystems: Integrating AI, Robotics, and Sustainability Through Digital Technologies

Abstract

The transformation of construction into an intelligent, digitally integrated ecosystem requires the coordinated application of artificial intelligence (AI), robotics, machine learning, data platforms, and sustainability-oriented decision processes. This review-oriented research paper develops a conceptual framework for intelligent construction ecosystems by examining how AI-enabled analytical capabilities can be integrated with robotic execution, digital data infrastructures, and risk-aware operational management. Because the supplied literature primarily addresses machine learning, data-driven detection, cybersecurity, and intelligent analytical systems rather than construction directly, the study positions these contributions as transferable technological foundations rather than as construction-specific empirical evidence. The literature demonstrates the value of feature-based machine learning, logistic regression, deep learning, cloud-oriented data processing, and systematic analytical approaches for converting complex digital data into actionable decisions (Das Guptta et al., 2022; Gupta and Mahajan, 2022; Kalla et al., 2023). Building on these technological principles, the paper proposes an intelligent construction ecosystem comprising five interconnected layers: data acquisition, intelligent analytics, robotic and automated execution, sustainability optimization, and cybersecurity/governance. The analysis indicates that successful digital construction cannot depend on isolated AI or robotic applications; instead, interoperability, data quality, cybersecurity, human oversight, and lifecycle sustainability must be treated as integrated design requirements. The resulting framework provides a theoretical basis for future empirical research involving construction-specific datasets, autonomous equipment, digital twins, and sustainability metrics.