Timeframe:
Spring 2018 – Present
Students:
Farah Jaradat (Alumni), Armando Pinales (Alumni), Fairuz Saeed, Adenrele Ishola
Faculty in Collaboration:
Dr. Bill Stapleton, Dr. Semih Aslan, Dr. Vishu Viswanathan
Overview:
The goal of this project is to accomplish the Machine Learning components and Embedded hardware design for Fire Safety decisions as a Smart City concept. The project is a sub-component of a dynamic infrastructure environment for fire hazard situations with environmental sensors, CNN+Computer Vision, audio pattern recognition, forecasting, and autonomous embedded units.
Stages
1. Early protocol designs
2. CNN person classification through IR Images
3. Senior Design
4. Scream Detection
5. Forecast of Temperature and Carbon Monoxide
Publications:
- F. B. Jaradat and D. Valles, “A Victims Detection Approach for Burning Building Sites Using Convolutional Neural Networks,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0280-0286, doi:10.1109/CCWC47524.2020.9031275
- F. Jaradat, D. Valles, “A Human Detection Approach for Burning Building Sites Using Deep Learning Techniques,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Computational Intelligence (CSCI-ISCI’18), Las Vegas, NV, 2018, pp 1434-1435, doi:10.1109/CSCI46756.2018.00277.
- A. Pinales, D. Valles, “AESV Integration of IMU and Implementation of Interleaved Data Acquisition and Transmission Method,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Smart Cities and Smart Mobility (CSCI-ISSC’18), Las Vegas, NV, 2018, pp. 541-544, doi:10.1109/CSCI46756.2018.00110.
- A. Pinales, D. Valles, “Autonomous Embedded System Vehicle Design on Environmental, Mapping and Human Detection Data Acquisition for Firefighting Situations,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 194-198, doi:10.1109/IEMCON.2018.8615022.
- F. Jaradat, D. Valles, “An Exponential Smoothing Embedded System Approach to Dangerous Temperature Detection for Firefighter Safety,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 41-44, ISBN: 1-60132-475-8.
Posters:
- F. Jaradat, D. Valles, “A Human Detection Approach for Burning Building Sites Using Deep Learning Techniques,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Computational Intelligence (CSCI-ISCI’18), Las Vegas, NV, 2018
- A. Pinales, D. Valles, “Autonomous Embedded System Design on Environmental, Mapping and Human Detection Data Acquisition for Firefighting Situations,” The 2018 SACNAS – The National Diversity in STEM Conference, San Antonio, TX, 2018
Thesis:
- Jaradat, F. B. (2019). A victims detection approach for burning building sites using convolutional neural networks (Unpublished thesis). Texas State University, San Marcos, Texas.
- Two to finish in Fall 2021
