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Sobre
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Sobre

Marco Amaro Oliveira tem um Mestrado em Sistemas de Informação e é aluno de Doutoramento em Engenharia Informática. Os seus interesses de Investigação e desenvolvimento são em Sistemas de Informação Complexos, Sistemas de Sistemas, Interoperabilidade de Sistemas e em Informação Espacio-Temporal.
Desde 2000 que desenvolve no INESC TEC atividades de investigação e gestão de projectos em diversos projetos de I&D, auditoria e transferência de conhecimento.
É Professor convidado no Instituto Universitário da Maia desde 2003.
Em 2015 co-fundou a MitMyNid, Lda. uma startup aliceçada em conhecimento e experiência para melhorar os Serviços de Logística com uma solução complementar  e adaptável a todos os aspectos dos serviços de transporte.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Marco Amaro Oliveira
  • Cluster

    Informática
  • Cargo

    Investigador Auxiliar
  • Desde

    20 julho 2000
004
Publicações

2020

I2B+tree: Interval B+ tree variant towards fast indexing of time-dependent data

Autores
Carneiro, E; Carvalho, AVD; Oliveira, MA;

Publicação
2020 15th Iberian Conference on Information Systems and Technologies (CISTI)

Abstract

2020

The 4-corner model as a synchromodal and digital twin enabler in the transportation sector

Autores
Carvalho, A; Melo, P; Oliveira, MA; Barros, R;

Publicação
2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)

Abstract

2018

Single window for collaborative multimodal logistics services an optimized and integrated door-to-door services offer

Autores
Oliveira, MA; Barros, RS; De Carvalho, AV; Melo, PR;

Publicação
2017 International Conference on Engineering, Technology and Innovation: Engineering, Technology and Innovation Management Beyond 2020: New Challenges, New Approaches, ICE/ITMC 2017 - Proceedings

Abstract
The development of a single window system for collaborative Multimodal Logistics services with offer for optimized and integrated door-to-door services is a complex endeavor. The concept was previously worked on by a set of European projects whose results were taken as best practices and lessons learned from the logistics sector. In this current paper we present a background and the major problems faced by the logistics sector and how IT can address them, and the existing expectations for collaborative real time door-to-door logistics Services. Next, we present the main results, consisting of an innovative system addressing these expectations - the Logistics Single Window. Finally we draw the conclusions from the results and present how the results innovate when compared with current state of the art. © 2017 IEEE.

2016

Efficient Delivery of Forecasts to a Nautical Sports Mobile Application with Semantic Data Services

Autores
Amorim, RC; Rocha, A; Oliveira, MA; Ribeiro, C;

Publicação
Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, C3S2E '16, Porto, Portugal, July 20-22, 2016

Abstract
Weather and sea-related forecasts provide crucial insights for the practice of nautical sports such as surf and kite surf, and mobile devices are appropriate interfaces for the visualization of meteorology and operational oceanography data. Data are collected and processed by several agencies and are often obtained from forecast models. Their use requires adaptation and refinement prior to visualisation. We describe a set of semantic data services using standard common vocabularies and interoperable interfaces following the recommendations of the INSPIRE directive. NautiCast, a mobile application for forecast delivery illustrates the adaptation of data at two levels: 1) semantic, with the integration of data from different sources via standard vocabularies, and 2) syntactic, with the manipulation of the spacial and temporal resolution of data to get effective mobile communication. Copyright 2016 ACM.

2014

Improvements to Efficient Retrieval of Very Large Temporal Datasets with the TravelLight Method

Autores
de Carvalho, AV; Oliveira, MA; Rocha, A;

Publicação
PROCEEDINGS OF THE 2014 9TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI 2014)

Abstract
A considerable number of domains deal with large and complex volumes of temporal data. The management of these volumes, from capture, storage, search, transfer, analysis and visualization, still provides interesting challenges. One critical task is the efficient retrieval of data (raw data or intermediate results from analytic tools). Previous work proposed the TravelLight method which reduced the turnaround time and improved interactive retrieval of data from large temporal datasets by exploring the temporal consistency of records in a database. In this work we propose improvements to the method by adopting a new paradigm focused in the management of time intervals instead of solely in data items. A major advantage of this paradigm shift is to enable the separation of the method implementation from any particular temporal data source, as it is autonomous and efficient in the management of retrieved data. Our work demonstrates that the overheads introduced by the new paradigm are smaller than prior overall overheads, further reducing the turnaround time. Reported results concern experiments with a temporally linear navigation across two datasets of one million items. With the obtained results it is possible to conclude that the improvements presented in this work further reduce turnaround time thus enhancing the response of interactive tasks over very large temporal datasets.