Structural Design Of The Nexx Building And Landslide Early Warning Based On Surface Crack Detection Using Deep Learning And Computer Vision

Abstract

In this thesis project, tall building – one of the most invested place for living – will be the main objective. Structural design like slab, beams, walls, foundations, will be process in detail in order to describe the design steps. The first step will begin with architecture drawing to the final is producing detail drawing for each structure including slab, beam, and column. And the other part is Landslide early warning based on surface crack detection using deep learning and computer vision. As for special topics, there are many types in this project showing the differences between of methods in order to provide the most efficient constructing choice. For instance, wind force will be calculated according to EN-1991 (Euro code), slab design will be carried out in form of flat slab with panel and solid slab, column design in 1 specific methods which are force analysis method, compared interaction diagram method. Besides, the design of beams in 2 distinct frames are choosen the internal from taken from Etabs sofware. Along with the design report is drawing used to express structural designed from those files in detail. They include architect drawing, slabs reinforcement, and frame design and be drawn by Revit Structure software, also supported by Naviate tool. The research is of Landslide early warning based on surface crack detection is a new method which rarely appears in Vietnam will also be described in detail for scientific research, which is using deep learnning- Yolov8 combined with Google collab to detection crack of ground surface; Canny Edge detection method to measure the edge of the crack, and Euler distance method to identify the width and length of the crack.