
Earthquake Waveform Prediction and Building Safety Assessment
Project Overview
The team builds ML models that forecast seismic signals and evaluate building safety using IS 1893 and IS 456 guidelines.
Tech Stack
Team
Mentors
- Sushanth
- Amarnath
- Charan
- Darshan
Mentees
No mentees listed for this project.
Problem Statement
Conventional monitoring lacks practical prescriptive safety advice and low-cost structural assessment tools.
Objectives
- - Build low-cost warning and structural safety tool
- - Predict PGA/PGV and representative waveforms
- - Assess safety via IS 1893 and IS 456 checks
- - Provide immediate safe/unsafe guidance
Methodology
The project follows a structured implementation approach that includes Process IRIS/FDSN seismic data with ObsPy, Train regression and sequence models for seismic prediction, Compute code-based base shear and capacity checks, and Deploy interactive low-cost web app. These steps are executed iteratively to validate assumptions, improve performance, and ensure reliable delivery of the final solution.
Expected Outcome
By the end of this project, the team is expected to deliver Seismic parameter prediction with actionable interface, and Practical safety verdict system. Together, these outcomes reflect both technical feasibility and practical value for demos, evaluation, and future scaling.
Future Scope
- - Global scale dataset expansion
- - IoT vibration monitoring integration
- - Additional structural indicators and adaptive learning