International Journal of Media and Networks(IJMN)
ISSN: 2995-3286 | DOI: 10.33140/IJMN
Impact Factor: 1.02
Researchers and authors can directly submit their manuscript online through this link Online Manuscript Submission.
AI-Driven Structural Health Monitoring: Unleashing Potential and Embracing Future Opportunities
Abstract
Royana Anand
Structural Health Monitoring (SHM) is a critical aspect of ensuring the safety and longevity of infrastructure such as bridges, buildings, and dams. Traditional SHM techniques, while effective, often rely on manual inspections and can be labor- intensive, time-consuming, and prone to human error. Recent advancements in Artificial Intelligence (AI) have the potential to revolutionize SHM by automating data analysis, improving predictive capabilities, and enhancing overall system efficiency. This article explores the integration of AI in SHM, highlighting key innovations, challenges, and future directions for this transformative technology.