Earthquake Waveform Prediction and Building Safety Assessment
ConcreteIn Progress2025-26

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

PythonMachine LearningSeismic Analysis

Team

Mentors

  1. Sushanth
  2. Amarnath
  3. Charan
  4. 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