Models for Person Recognition and Identification Using a Security Camera in Embedded Systems

This project focuses on applying advanced facial recognition technologies to mitigate the aggravated robbery rate in Guayaquil. The methodological approach is structured into four key phases. Initially, an exhaustive literature review will be conducted on embedded systems and the state-of-the-art in facial recognition techniques and associated technologies. Subsequently, embedded software will be developed and implemented on specific hardware devices to enable individual recognition. The crucial phase involves deploying this system within public transportation means. The ultimate goal is to utilize this technology to identify individuals with illegal or criminal records in real-time, thereby contributing to public safety. The project coordinator brings prior expertise in Machine Learning, specifically in Evolutionary Artificial Neural Networks and Extreme Machine Learning, which underpins the technical development of the solution.<br/><br/><b>Goal</b>: <br/>Positively reduce the aggravated robbery rate in the city of Guayaquil through the implementation of automatic facial recognition technologies.<br/><br/><b>Research lines</b>: <br/>Computer systems and artificial intelligence