با همکاری مشترک دانشگاه پیام نور و انجمن جغرافیا و برنامه ریزی روستایی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری معماری، واحد یاسوج، دانشگاه آزاد اسلامی، یاسوج، ایران

2 دانشیار گروه معماری و شهرسازی، واحد یاسوج، دانشگاه آزاد اسلامی، یاسوج، ایران

3 استادیار معماری، دانشکده فنی و مهندسی دانشگاه یاسوج، یاسوج، ایران

4 استادیار گروه مهندسی کامپیوتر، واحد یاسوج، دانشگاه آزاد اسلامی، یاسوج، ایران

10.30473/psp.2024.67927.2673

چکیده

مدل‌سازی اطلاعات ساختمان (BIM) صنعت ساخت‌وساز را با بهبود کارایی و ساده‌سازی روش‌های پروژه ساختمان متحول ساخته است.ادغام BIM با سیستم‌های دیجیتالی همچون هوش‌مصنوعی (AI) ، موانع را از بین ‌برده و چرخه عمر پروژه را سازنده‌تر و سودمندتر می‌سازد. مزایای BIM و AI فراتر از مدل‌سازی سه بعدی و طرح‌های ساختمانی است. آن‌ها کل چرخه عمر پروژه ساخت‌و‌ساز را از صفر به بعد مدیریت و کنترل می‌کنند. هدف این پژوهش ارائه درک جامع از روند ادغام AI-BIM است که توسط محققان مختلف در سراسر جهان انجام شده است. دستیابی به این هدف از طریق تحلیل نظام وار 380 مقاله انتشار یافته در سال‌های 2015-2021 از طریق پایگاه استنادی اسکوپوس است این پژوهش مروری نظام وار از تحقیقات کیفی را برای تشخیص ویژگی‌های BIM، AI، ادغام و پیاده‌سازی آن‌ها در ساخت‌و‌ساز ارائه می‌کند. همچنین روندها و بینش‌های تحقیقاتی آینده را ارائه داده و بر قابلیت همکاری در BIM تأکید می‌کند. در بخش دیگر، نیاز به تحقیقات آینده را برای تمرکز بر قابلیت همکاری هوش‌مصنوعی و سایر سیستم‌های هوشمند در BIM را برای تقویت علم یکپارچه بر اساس دیجیتالی شدن و فناوری اطلاعات و ارتباطات تقویت می سازد.در نهایت گسترش یافته ها را نیز در طول چرخه عمر پروژه ساخت‌وساز ساختمان برجسته می‌کند. نتایج تحلیل نظام وار دراین تحقیق نشان می‌دهد که ادغام هوش‌مصنوعی و BIM ظرفیت تغییر صنعت ساخت‌و‌ساز را در بر دارد. زیرا توانایی کاهش قابل توجهی از خطاها ،صرفه جویی در زمان و منابع (نیروی انسانی و مصالح ساختمانی) ، افزایش بهره‌وری و متناسب سازی نقشه را بر اساس نیاز کاربر با استفاده از سه ماژول کنترل کننده، پایگاه داده و یادگیری ماشین و با توجه به مقررات ساختمانی را دارد. این پژوهش همچنین برخی از چالش‌هایی مانع  از ادغام هوش‌مصنوعی و BIM را همچون فقدان استانداردهای قابلیت همکاری، نگرانی‌های مربوط به حریم خصوصی داده‌ها و آموزش ناکافی برای متخصصان را شناسایی می‌کند. 

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