Intelligent construction refers to the integration of digital tmodechnologies, data-driven methods, artificial intelligenceling, sensor networks, automation, and automated systemdata analytics throughout the building life cycle to improve the planning, design, construction, and operation of built assets. It encompasses building information modeling (BIM), Internet of Things (IoT), digital twins, artificial intelligence (AI), machine learning, robotics, andgenerate, manage, and share a computable digital representation of a physical facility that supports design, construction automation, which can be combined to support information integ, and operation, monitoring, analysis,al decision-making, and automated or semi-automated construction processes ^[1][2]. RatTher than referring to a single foundational technology, intelligent construction represents an integrated approach in is building information modeling, which digital information and computatcreates a three-dimensional technologies are used to improve construction processes, productivity, safety, qualityobject-oriented model embedding geometric, material, cost, schedule, and decision-making across the project life cycle ^[1]. BIM provides sperformance data, and extructured digital information about building components and project processes, while IoT devices, snds it with real-time data from site sensors, reality-capture technologiInternet-of-Things devices, and other data sources can provide information about the physical construction environment. These data can be integrated intoterrestrial laser scanning to form a digital twins to establish connections between that synchronizes the physical assets and their digital representations, supporting applications such as consconstruction progress monitoring, quality control, safety management, resource and logistics management, and predictivcess with its virtual model in near real time analysis ^[2][3]. AI and macThine learning can be applied to tasks such as cost and schedule prediction, risk assessment, image-based quality inspection, safety monitoring, and decision support ^[4]. Robote approach supports automated quantity takeoff, multi-disciplics and automated construction systems further extend intelligentary clash detection, construction from digital analysis to physical execution, including automated material handling, robotic assembly, autonomous construction equipment, inspection, and human–robot collaborprogress tracking, resource allocation ^[5]. The imoplementation of intelligent construction faces technical, organimizational, and workforce-related challenges. Data quality, interoperability, and data integration can affect the reliability and scalability of systems that combine BIM, IoT, digital twins, AI, and robotic technologpredictive safety monitoring, and it relies ^[2][3]. Differeonces in data structures and software platforms may hinder informationstandardized open data exchange across project participants, while insufficient data quality can reduce the reliability of AI-based analysis and digital-twin applicationsschemas such as the Industry Foundation ^[2][3]. ImpClementation may also require substantial investment in digital infrastructure, changes to established workflows, and personnel with appropriate digital, analytical, and technical skillsses to enable interoperability across ^[1][3]. Thdifferefore, intelligent construction depends not only on the adoption of individual technologies but also on their effective integration with software platforms and among all participating project processes, information management, and human expertisestakeholders throughout the building life cycleentire built facility lifecycle ^[3].