High-rise façades are critical components of modern urban infrastructure, subject to wear and tear due to environmental factors, age, and construction defects. Traditional manual inspection methods for these façades are labor-intensive, time-consuming, and often prone to human error. This paper proposes an innovative approach for automated defect detection in high-rise façades using drone-based inspections combined with Artificial Intelligence (AI) techniques. By leveraging drones equipped with high-resolution cameras and AI-driven image processing, we demonstrate the ability to efficiently identify defects such as cracks, water ingress, and structural damage. The integration of machine learning algorithms enhances the accuracy and speed of the inspection process, reducing the need for human intervention and improving safety. The proposed system offers significant improvements in monitoring the condition of high-rise buildings, enabling proactive maintenance and minimizing the risk of costly repairs or safety hazards.
Md Shoag (Fri,) studied this question.