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Publications

2022

Anda: An Innovative Micro-Location Mobile Ticketing Solution Based on NFC and BLE Technologies

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

Best Frame Selection to Enhance Training Step Efficiency in Video-Based Human Action Recognition

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.

2022

Binaural Acoustic Scene Classification Using Wavelet Scattering, Parallel Ensemble Classifiers and Nonlinear Fusion

Authors
Hajihashemi, V; Gharahbagh, AA; Cruz, PM; Ferreira, MC; Machado, JJM; Tavares, JMRS;

Publication
SENSORS

Abstract
The analysis of ambient sounds can be very useful when developing sound base intelligent systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded sound or clip among some predefined scenes. ASC has huge potential to be used in urban sound event classification systems. This research presents a hybrid method that includes a novel mathematical fusion step which aims to tackle the challenges of ASC accuracy and adaptability of current state-of-the-art models. The proposed method uses a stereo signal, two ensemble classifiers (random subspace), and a novel mathematical fusion step. In the proposed method, a stable, invariant signal representation of the stereo signal is built using Wavelet Scattering Transform (WST). For each mono, i.e., left and right, channel, a different random subspace classifier is trained using WST. A novel mathematical formula for fusion step was developed, its parameters being found using a Genetic algorithm. The results on the DCASE 2017 dataset showed that the proposed method has higher classification accuracy (about 95%), pushing the boundaries of existing methods.

2022

Restart: A Route Planner to Encourage the Use of Public Transport Services in a Pandemic Context

Authors
Fulgêncio, R; Ferreira, MC; Abrantes, D; Coimbra, M;

Publication
Transportation Research Procedia

Abstract
Public transport services play an important role in the mobility of the population in urban centers, allowing a decrease in the number of private vehicles in circulation and contributing to a more sustainable mobility. However, the emergence of the COVID-19 pandemic had a serious impact on the mobility habits of the population, with a substantial reduction in the number of public transport passengers due to the fear of contagion, which raises questions about the future sustainability of cities. Thus, it is essential to restore the confidence of travelers to feel safe and comfortable using public transport services. Taking advantage of the widespread use of mobile technologies, this article intends to propose a route planning system for public transport that meets the needs of passengers in terms of safety and comfort. After a systematic review of the existing literature and a series of focus group sessions, a prototype of the system was developed, and subsequently evaluated by potential users through usability tests. The results obtained are a good indicator of the system's functionality and ease of use. This assessment allowed us to corroborate the potential that the proposed route planning system has in promoting the use of public transport services as a means of mobility.

2022

Tourism as a Service: Enhancing the Tourist Experience

Authors
Mendes, B; Ferreira, MC; Dias, TG;

Publication
Transportation Research Procedia

Abstract
The tourism sector has been facing continuous growth. It plays a vital role in countries' economic development, highlighting the need to keep nurturing it by making it easier and more attractive. This paper presents Tourism as a Service - an innovative concept that aims to ease a day in the life of a tourist by integrating services that might be found spread out through separate tools and services, including ticketing in public transport and touristic attractions, route planning, information, among others. First, focus groups were done in order to understand the users' needs regarding the use of a mobile ticketing solution in tourism. The findings from the literature reviewed and the previous step were then prioritized by relevance in a questionnaire sent to potential users, allowing the creation of a medium-fidelity prototype. The validation through usability testing confirmed an interest in the proposed solution. The critical design choices surrounding the proposed solution were discussed along with improvements and further work to be done.

Supervised
thesis

2017

Dependable and Decentralized Software-Defined Storage Stack

Author
Ricardo Gonçalves Macedo

Institution
UM

2016

Cavity Ring-down Characterization Technique

Author
regina Magalhâes

Institution
UP-FCUP

2016

A maturidade do mercado através da evolução tecnológica: o caso dos Smartwatches

Author
Simão Martins Almeida

Institution
UP-FEP