0000000000722635
AUTHOR
Nabil Belbachir
Enhancing Disaster Response for Hazardous Materials Using Emerging Technologies: The Role of AI and a Research Agenda
Despite all efforts like the introduction of new training methods and personal protective equipment, the need to reduce the number of First Responders (FRs) fatalities and injuries remains. Reports show that advances in technology have not yet resulted in protecting FRs from injuries, health impacts, and odorless toxic gases effectively. Currently, there are emerging technologies that can be exploited and applied in emergency management settings to improve FRs protection. The aim of this paper is threefold: First, to conduct scenario analysis and situations that currently threat the first responders. Second, to conduct gap analysis concerning the new technology needs in relations to the pro…
A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
Aerial inspection of solar modules is becoming increasingly popular in automatizing operations and maintenance in large-scale photovoltaic power plants. Current practices are typically time-consuming as they make use of manual acquisitions and analysis of thousands of images to scan for faults and anomalies in the modules. In this paper, we explore and evaluate the use of computer vision and deep learning methods for automating the analysis of fault detection and classification in large scale photovoltaic module installations. We use convolutional neural networks to analyze thermal and visible color images acquired by cameras mounted on unmanned aerial vehicles. We generate composite images…