Details
Name
Marta Campos FerreiraCluster
Industrial and Systems EngineeringRole
ResearcherSince
01st January 2014
Nationality
PortugalCentre
Industrial Engineering and ManagementContacts
+351 22 209 4190
marta.c.ferreira@inesctec.pt
2023
Authors
Abrantes, D; Ferreira, MC; Costa, PD; Hora, J; Felício, S; Dias, TG; Coimbra, M;
Publication
International journal of environmental research and public health
Abstract
2023
Authors
Barros, D; Ferreira, MC; Silva, AR;
Publication
Advances in Transportation Studies
Abstract
Nowadays, cities face severe problems related to traffic management and mobility in general. Therefore, technologies have been developed that can handle these situations and somehow mitigate the caused impact, such as CCTV cameras. However, the techniques for analyzing the images collected by these cameras are increasingly complex and have numerous applications, being dispersed in the literature. Therefore, this article fills an important research gap by presenting a systematic review of the literature on the possible applications of data collected from CCTV cameras and the image analysis and processing techniques that have been developed and proposed in recent years. This systematic review followed the PRISMA statement guidelines and checklist, and three databases were searched, namely Scopus, Web of Science, and Inspec. From the analysis performed, the following applications were identified: Image/video analysis and traffic estimation, pedestrian detection, traffic data analysis, and forecasting, and traffic management. Regarding the image analysis and processing techniques YOLO (only look once), GMM (Gaussian mixture method), morphological methods, fuzzy logic, and other proprietary methods stand out. After a thorough analysis of traffic data, most works still implemented relatively trivial traffic management systems to generate a series of actions to be eventually applied to traffic controllers. Additionally, it was realized that these techniques could be implemented in industrial products from a future perspective. © 2023, Aracne Editrice. All rights reserved.
2023
Authors
Felício, S; Hora, J; Ferreira, MC; Abrantes, D; Luna, F; Silva, J; Coimbra, M; Galvão, T;
Publication
Wireless Mobile Communication and Healthcare
Abstract
2022
Authors
Ferreira, MC; Dias, TG; Cunha, JFE;
Publication
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Abstract
Mobile ticketing services allow urban transport passengers to travel in a convenient and easy way, enhancing their travelling experience. In recent years several mobile ticketing services have started to be developed and launched, but there is still a lot to be done in terms of its effectiveness, efficiency and innovation. This paper presents a micro-location mobile ticketing solution based on Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technologies, called Anda. This solution is based on a check-in/be-out scheme and requires the minimum intervention from the passenger. It is really innovative in the urban transport field, as it takes advantage of BLE technology not usually used for this purpose, it is based on a concept of post-billing with a fare optimization algorithm associated and it allows the micro-location of passengers throughout their journeys. This paper details the architecture of the solution and its mode of operation. It also presents the evaluation methodology that was followed during the pilot trial that took place in the Metropolitan Area of Porto (AMP), Portugal, during one year with 140 real passengers. A set of design lessons were identified as a result of the field tests and materialized in five mobile ticketing design dimensions, constituting important contributions to the design of future mobile ticketing services. Anda was commercially deployed in the AMP in 2018 and is used by thousands of passengers every day. IEEE
2022
Authors
Gharahbagh, AA; Hajihashemi, V; Ferreira, MC; Machado, JJM; Tavares, JMRS;
Publication
APPLIED SCIENCES-BASEL
Abstract
In recent years, with the growth of digital media and modern imaging equipment, the use of video processing algorithms and semantic film and image management has expanded. The usage of different video datasets in training artificial intelligence algorithms is also rapidly expanding in various fields. Due to the high volume of information in a video, its processing is still expensive for most hardware systems, mainly in terms of its required runtime and memory. Hence, the optimal selection of keyframes to minimize redundant information in video processing systems has become noteworthy in facilitating this problem. Eliminating some frames can simultaneously reduce the required computational load, hardware cost, memory and processing time of intelligent video-based systems. Based on the aforementioned reasons, this research proposes a method for selecting keyframes and adaptive cropping input video for human action recognition (HAR) systems. The proposed method combines edge detection, simple difference, adaptive thresholding and 1D and 2D average filter algorithms in a hierarchical method. Some HAR methods are trained with videos processed by the proposed method to assess its efficiency. The results demonstrate that the application of the proposed method increases the accuracy of the HAR system by up to 3% compared to random image selection and cropping methods. Additionally, for most cases, the proposed method reduces the training time of the used machine learning algorithm. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Supervised Thesis
2018
Author
José Miguel Botelho Mendes
Institution
UP-FEUP
2018
Author
Luís Miguel Azevedo Duarte
Institution
UP-FEUP
2018
Author
Daniel Meireles de Amorim
Institution
UP-FEUP
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