The rapid growth of aquaculture infrastructure in coastal regions has brought unprecedented challenges in maintaining the structural integrity and sustainability of facilities such as fish tanks, ponds, water containment barriers, and associated civil structures. Traditional monitoring methods often fall short in providing timely and accurate assessments necessary to prevent structural failures that can lead to significant economic losses and environmental degradation. This study proposes an advanced AI-driven Structural Health Monitoring (SHM) framework specifically designed for aquaculture infrastructure in coastal environments.
The proposed system integrates a network of state-of-the-art sensors, including strain gauges, corrosion detectors, and environmental sensors, with sophisticated machine learning algorithms capable of analyzing vast amounts of real-time data. This combination enables continuous monitoring and early detection of structural anomalies induced by factors such as saltwater corrosion, wave impact, soil erosion, and extreme weather events like cyclones and floods. By leveraging predictive analytics, the AI system forecasts potential failure points and deterioration trends, facilitating timely maintenance interventions.
Furthermore, this proactive maintenance approach minimizes operational downtime and repair costs, while significantly reducing the risk of catastrophic failures that can adversely affect aquatic ecosystems and local livelihoods. The implementation of such intelligent SHM systems aligns with sustainable engineering practices by optimizing material usage, extending infrastructure lifespan, and promoting environmental conservation.
Through field trials and simulations conducted in representative coastal aquaculture sites in India, the study demonstrates the effectiveness of the AI-based SHM framework in enhancing the resilience and sustainability of aquaculture infrastructure. The integration of civil engineering expertise with cutting-edge AI technology presents a transformative strategy to support the scalable and sustainable expansion of the aquaculture industry, ensuring food security, economic growth, and ecological balance in India’s coastal regions.
KEYWORDS: · Artificial Intelligence (AI),Structural Health Monitoring (SHM), Aquaculture Infrastructure, · Sustainable Engineering, · Civil Engineering, Environmental Monitoring