Year: 2025
Type: article
Abstract: Civil infrastructures such as buildings, bridges, and dams are constantly exposed to environmental stresses, including temperature fluctuations, moisture variations, and material deterioration, which can gradually lead to cracks and structural weaknesses. Even minor cracks, if undetected, can evolve into serious hazards, compromising safety and stability. Traditional manual inspection methods are time-consuming and often fail to identify early-stage defects, delaying maintenance and increasing repair costs. To overcome these challenges, automated wall crack detection systems have been developed, integrating sensors, image processing, and real-time monitoring to continuously assess structural health. These systems can detect both visible and micro-cracks with high accuracy, providing instant alerts to maintenance teams for timely intervention. By analyzing trends in crack formation, predictive maintenance becomes possible, allowing engineers to plan repairs efficiently and reduce unnecessary expenses. The integration of IoT technology enables remote monitoring, data storage, and long-term performance evaluation. Automated monitoring also reduces human error, improves reliability, and ensures compliance with safety standards. Civil infrastructures equipped with such systems experience extended lifespans, improved safety, and enhanced durability against environmental and operational stresses. Early detection minimizes the risk of catastrophic failures, promotes sustainable maintenance practices, and supports data-driven engineering decisions. Overall, this approach bridges civil engineering with modern technology, offering a cost-effective, efficient, and intelligent solution for structural health management. By enabling proactive maintenance, reducing inspection costs, and ensuring safer environments, early wall crack detection contributes significantly to the resilience, sustainability, and longevity of civil infrastructure
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416540339