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About

I have a degree in Environmental Engineering (UFP, 2001) and in Informatic Engineering (ISEP, 2007). In 2010 I received a PhD degree in Environmental Sciences (Univ. of Aveiro, 2010).

 

I have 15 years’ experience in conducting research and consultancy projects (e.g. Seamless Mobility, SmartDecision, CIVITAS-ELAN). During the last years I published more than 20 papers in peer-review journals, and 50 publications in national and international congresses. 

My research expertise is in Transportation and Environmental systems, with emphasis on the analysis and development of transport policies. I'm competent in the use of different methods of monitoring and modeling air quality and road traffic systems.

In recent years I have participated in several Action Costs as ARTS, TEA and TRANSITS. In 2016 I spent 6 months in Beijing to study the impacts of road traffic policies in the air quality of the city.

Interest
Topics
Details

Details

001
Publications

2020

Design of a Route-Planner for Urban Public Transport, Promoting Social Inclusion

Authors
Dias, R; Fontes, T; Galvão, T;

Publication
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Abstract
People that do not have access to the transport system and therefore, a facilitated access to goods and services essential to daily life, can be regarded as transport-related social excluded. This is a big issue, namely for groups of people that have physical, sensorial and/or cognitive limitations. This paper provides guidelines to design route planners for socially excluded groups, by promoting social inclusion in public transportation. For this purpose, a set of mock-up user-interfaces of an inclusive inter-modal route planning application were developed. These interfaces will deliver ready availability of information about infrastructures and other journey related data. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

2020

Process discovery on geolocation data

Authors
Ribeiro, J; Fontes, T; Soares, C; Borges, JL;

Publication
Transportation Research Procedia

Abstract

2020

A Deep Learning Approach for Predicting Bus Passenger Demand Based on Weather Conditions

Authors
Fontes, T; Correia, R; Ribeiro, J; Borges, JL;

Publication
Transport and Telecommunication Journal

Abstract
AbstractThis work apply a deep learning artificial neural network model – the Multilayer Perceptron – as a regression model to estimate the demand of bus passengers. Transit bus ridership and weather conditions were collected over a year from a medium-size European metropolitan area and linked under the assumption: individuals choose the travel mode based on the weather conditions that are observed during (a) the departure hour, (b) the hour before or (c) two hours prior to the travel start. The transit ridership data were also labelled according to the hour of the day, day of the week, month, and whether there was a strike and/or holiday or not. The results show that the prediction error of the model decrease by ~9% when the weather conditions observed two hours before travel start is taken into account. The model sensitivity analyses reveals that the worst performance is obtained for a strike day of a weekday in spring (typically Wednesdays or Thursdays).

2019

Prediction of Journey Destination for Travelers of Urban Public Transport: A Comparison Model Study

Authors
Costa, V; Fontes, T; Borges, JL; Dias, TG;

Publication
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Intelligent Transport Systems, From Research and Development to the Market Uptake

Abstract

2019

Environmental and biological monitoring of benzene, toluene, ethylbenzene and xylene (BTEX) exposure in residents living near gas stations

Authors
Barros, N; Carvalho, M; Silva, C; Fontes, T; Prata, JC; Sousa, A; Conceicao Manso, MC;

Publication
JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH-PART A-CURRENT ISSUES

Abstract
The volatile organic compounds benzene, toluene, ethylbenzene, and xylene (BTEX) are emitted into the atmosphere at gas stations (GS) leading to chronic exposure of nearby residents, which raises public health concerns. This study aimes at determining the contribution of GS emissions to BTEX exposure in nearby residents. Three Control and Exposed areas to BTEX emissions from GS were defined in a medium-sized European city (Porto, Portugal). BTEX atmospheric levels were determined in Control and Exposed areas using passive samplers deployed outdoors (n = 48) and indoors (n = 36), and human exposure was estimated for 119 non-smoking residents using the first urine of the day. Results showed that median BTEX outdoor and indoor concentrations were significantly higher for Exposed than Control areas, with exception of ethylbenzene and xylene indoor concentrations, where no marked differences were found. Comparison of urinary concentrations between Exposed and Control residents demonstrated no significant differences for benzene and ethylbenzene, whereas levels of toluene and xylene were significantly higher in Exposed residents. No marked correlation was obtained between atmospheric BTEX concentrations and urinary concentrations. Data indicate the potential impact on air quality of BTEX emissions from GS, which confirms the importance of these findings in urban planning in order to minimize the impact on health and well-being of surrounding populations.

Supervised
thesis

2019

Design of a route-planner for urban public transport, promoting social inclusion

Author
Rafael Marques Dias

Institution
UP-FEUP