Research on Intelligent Detection and Diagnosis of Civil Engineering Quality Driven by Artificial Intelligence

Abstract

The quality of civil engineering is related to the safety, durability and service efficiency of buildings. And the traditional detection
and diagnostic mode is dependent upon manpower; there are many significant issues like lack of efficiency, heavy subjective element, poor
ability in identifying concealed faults, hard-to-quantify traceability of data etc., thus it's hard to fulfill the need for modern large-scale civil
engineering in terms of quality control. The paper focuses mainly on the deep integration of AI tech and civil engineering quality detection,
which will improve detection accuracy, diagnose better and make the process more intelligent. And we fully explore its main application
roads, technical difficulties and new breakthroughs in the field of AI with respect to civil engineering quality detection and diagnostic. Carry
out theoretical analysis through the study and verification of the applicability based on actual application of important technical core theories
such as computer vision technology, deep learning technology, multi-mode data fusion etc., put forward improvement measures and give direction to develop in the future, provide a theoretical reference for converting the conversion from manual civil engineering quality inspection
to intelligent, also helps promote the transition in civil engineering quality supervision and inspection model from original mode converted to
intelligence early warning precise and efficient smart Early Warning Mode.