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DEI - FCTUC
Gerado a 2024-05-17 04:23:58 (Europe/Lisbon).
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Titulo Estágio

Smart Berth Planning for commercial ports

Áreas de especialidade

Sistemas Inteligentes

Sistemas de Informação

Local do Estágio

Laboratório de Informática Industrial e Sistemas do DEI/CISUC (LIIS@DEI-FCTUC)

Enquadramento

The transportation and logistics sector is seeking solutions for a digital transition. There is a need for more digital operations, particularly on the automation of processes and operations, in order to reduce the need for human interaction. This will contribute to reducing significantly existing inefficiencies. On the other hand, sustainability is also key and has been a trend in the last few years. The sector is being pressed for a green transition, since it is the second-largest source of greenhouse gas (GHG) emissions in the EU, with traffic expected to increase around 40% by 2050, according to the European Commission.
As a vital part of the transportation and logistics sector, Ports are no exception. They face several challenges regarding this double transition (i.e., digital and green transition), which represent great opportunities for research and innovation.
Among these challenges, there is a need for smarter berth planning. This master thesis is intended to research solutions to optimize berth planning, by incorporating predictive analytics to significantly improve decision making.

Objetivo

The main objectives of this thesis are as follows:
- Research and development of predictive models supported by machine learning techniques to drive smarter berth planning in commercial ports
- Integrate such models into a digital twin of a commercial port as a proof-of-concept.

Plano de Trabalhos - Semestre 1

The main phases for the first semester are presented as follows (may overlap):
1. Research the state-of-the-art using a systematic literature review [1,2] on predictive models based on machine learning techniques to support smart berth planning tools and process automation
Start: September 2022
Duration: 2 months
2. Identify and test existing algorithms that can be incorporated into smart berth planning tools
Start: November 2022
Duration: 1 month
3. Design the smart berth system taking into account the requirements specified in the previous steps
Start: November 2022
Duration: 2 months
Results of the 1st semester:
- Literature review on predictive models for smart berth planning
- Architecture for the berth planning system
- Intermediate report

References:
[1] Webster, J., Watson, R.T.: (2011). Analyzing the Past To Prepare for the Future: Writing a Review. MIS Quartely. 26 (2), 12.
[2] Kitchenham, B., Charters, S.: (2007). Procedures for Performing Systematic Literature Reviews in Software Engineering. Keele Univ. Durham Univ. UK.

Plano de Trabalhos - Semestre 2

The main phases for the second semester are presented as follows:
4. Develop and test a prototype to showcase the smart berth planning system
Start: January 2022
Duration: 4 months
5. Write the scientific paper and the master thesis
Start: May 2023
Duration: 2 months

Results of the 2nd semester:
- Berth planning system prototype
- Final report
- Scientific paper: Smart berth planning for commercial ports

Condições

The student will be integrated in the activities of CISUC (Adaptive Computation Group and Information Systems Group), Department of Informatics Engineering, University of Coimbra.
A workplace and the required resources will be provided.
The supervisors of the thesis will be:
- Prof. Alberto Cardoso
- Prof. Jacinto Estima

Observações

The internship may benefit from the award of a research grant for graduates for a period of 3 months, possibly renewable, supported by the ongoing projects.

Orientador

Alberto Cardoso
alberto@dei.uc.pt 📩