Machine Learning Algorithms for Structural Health Monitoring

Built deep learning models for Monitoring the Health of Building Structures which allows keeping track of structural damage using features like inter-story drift ratio and data from accelerometer signals. Used CNNs on simulated accelerometer data for classifying structural state based on damage. This can help address vulnerable structures and prevent the loss of life and property after a natural disaster. Worked on the project during my internship at CEERI Pilani. GITHUB