Digitized Fuel Load Survey Methodology Using Machine Vision

Fire Protection Research Foundation report: “Digitized Fuel Load Survey Methodology Using Machine Vision"
Authors: Negar Elhami-Khorasani, Juan Gustavo Salado Castillo, Esther Saula, Timothy Josephs, Gauhar Nurlybekova, University at Buffalo, The State University of New York; Thomas Gernay, Johns Hopkins Whiting School of Engineering
Date of issue: December 2019

Report

Digitized Fuel Load Survey Methodology Using Machine Vision

The report documents a new more efficient methodology using machine learning for fuel load surveys of buildings to facilitate the collection of data for performance based design.

Download the report.