Structural health monitoring (SHM) is vital for safeguarding infrastructure by identifying and addressing damage risks. Traditional methods, however, often struggle to deliver accurate real-time data on high-stress areas, like crack tips, where failure is most likely. These regions require careful monitoring to predict and prevent catastrophic structural failure. Yet, capturing the complexities of stress concentrations at crack tips remains a significant challenge. This study addresses these shortcomings by proposing a novel solution to achieve real-time structural assessments of pre-cracked structures.