Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE: CARLOS VICTOR SANTANA BRITO
DATA: 31/07/2024
HORA: 14:00
LOCAL: Plataforma Google Meet
TÍTULO: Performability Assessment of a Highway Video Monitoring System with Stochastic Petri Nets
PALAVRAS-CHAVES: Urban security landscapes, Surveillance systems, Analytical models, System performance, Smart cities
PÁGINAS: 82
GRANDE ÁREA: Ciências Exatas e da Terra
ÁREA: Ciência da Computação
SUBÁREA: Sistemas de Computação
ESPECIALIDADE: Software Básico
RESUMO:

The evolution of urban security landscapes within smart cities has been propelled by rapid technological advancements and the increasing need for robust security measures and efficient urban management. Surveillance systems, characterized by extensive networks of closed-circuit television (CCTV) cameras and sensor arrays, have emerged as pivotal components in this transformation. These systems not only monitor urban spaces comprehensively but also manage traffic patterns and ensure public safety. The integration of advanced functionalities such as facial recognition, motion detection, and AI-driven analytics has revolutionized these systems, enhancing their ability to detect anomalies and prevent potential incidents without constant human oversight. Despite their critical role, the deployment and maintenance of such systems pose significant challenges, including high operational costs and the complexity of managing vast amounts of video data. Addressing these challenges requires innovative approaches such as the application of analytical models during the design phase to predict system performance and availability metrics. Such models offer cost-effective alternatives to real-world testing, allowing stakeholders to optimize system configurations and operational strategies. This dissertation investigates the feasibility and methodology of using analytical models to predict the performance metrics and availability of urban video monitoring systems without the need for physical infrastructure. Key research objectives include evaluating system performance under varying operational conditions, assessing reliability through metrics such as uptime and response times, and exploring strategies to enhance system availability and maintainability. The study employs a multidisciplinary approach to enhance the efficacy and reliability of urban surveillance systems. By leveraging analytical modeling techniques, this research contributes to advancing the understanding of urban surveillance system dynamics and informs decision-making processes aimed at optimizing resource allocation and enhancing urban security in smart city environments.

MEMBROS DA BANCA:
Presidente - 1042211 - FRANCISCO AIRTON PEREIRA DA SILVA
Interno - 1732264 - JULIANA OLIVEIRA DE CARVALHO
Externo à Instituição - PAULO ANTONIO LEAL REGO - UFC
Externo à Instituição - PAULO ROMERO MARTINS MACIEL - UFPE

Cadastrada em: 11/07/2024