Offers in: Telecommunication Systems Engineering
Academic Supervisor:
Santiago M Olaizola
department Tecnun/Division CEIT:
Materials and Manufacturing Division: Precision Laser Manufacturing group.
area subject:
Industrial manufacturing processes
Description and objectives:
Our research activity is focused on laser processing of materials. For this purpose, we use ultra-short laser pulses (femtosecond lasers), capable of producing very precise Structures on material surfaces with a very high definition of the order of micrometer. This is made possible by the "cold ablation" processing regime. High definition surface textures can be used for a variety of applications, such as friction management, plastic injection molds, implants, metrology of self-cleaning objects, antennas, etc.
The research project offered in this group covers the fabrication, measurement and modeling of the Structures for a selected application. The specific nature of the project depends on the duration of the placement and the student's background. For example:
Industrial technologies engineering: laser modification of stainless steel to control surface hydrophobicity, design and laser process programming.
Telecommunication engineering: analysis of the predictability of periodic corrugations on surfaces produced by femtosecond lasers, analysis of results, laser beam control.
Field: laser applications
requirementsPhysics: solid knowledge of physics. Python programming skills are recommended.
Academic Supervisor:
Saioa Arrizabalaga
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area Thematic:
5G, Kubernetes, Cloud Computing, Virtualization.
Description and Objectives:
The adoption of Cloud Native in 5G telecom systems has been identified as a good candidate to reduce cost, improve system agility and the role of 5G services. Based on the 3GPP standard, the European Telecommunications Standards Institute (ETSI) has published the reference letter architecture of NFV adapted to Cloud Native environments and to enhance the framework of NFV, including, containers, load balancers and other elements as part of the architecture of reference letter.
This work pursues the validation of container technology on the MANO platform hosted at ETSI, in a CN environment, so that the results obtained in the work can help to encourage users and operators to use KNFs and thus taking advantage of container technologies.
Academic Supervisor:
Saioa Arrizabalaga
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Security.
Description and Objectives:
CI/CD is increasingly popular in embedded software development . However, projects are often constrained in a way that they are not in the development of applications (e.g., web). In addition to the physical and computational limitations of the target hardware platform, there are market limitations. The embedded software market has unique requirements security, privacy, and extremely long life cycles (e.g., products can remain on the market for decades). At the level of development, embedded software is not much different than development from typical applications (e.g., web), requiring IDEs, compilers, static and dynamic analysis and dynamics tools. However, the tools typically address architectures on which they work (host vs. target environment). Compiler-level automation uses the same techniques, but when code execution is involved, the host/target barrier becomes significant. Code execution automation requires special support development of software. Software test automation is more challenging due to the complexity of initiating and testing on embedded targets, not to mention the limited limited access to the target hardware that software teams have. This project, aims to carry out a first approach to the basic development CI/CD on embedded systems. Thus, given a basic development in C/C++, it is intended to pass this code through stages of testing, security checks and compilation (CI), to then perform an automated submission on a device (e.g. a microcontroller), but not before also performing functional testing (CD).
Academic Supervisor:
Saioa Arrizabalaga
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
Industrial process modeling. Cybersecurity.
Description and objectives:
Hybrid testbeds allow the study of offensive and defensive cybersecurity mechanisms in industrial environments and also their impact on the process being attacked or defended.
This project would be focused on the generation of digital twins for industrial systems (such as wind turbines, water distribution networks...), using existing Simulink models. The student will have to map sensors/actuators on the models, define operating states (normal, abnormal) to improve testbed monitoring and response capabilities, analyze potential system cybersecurity threats and develop mitigation strategies. Simulink models will be modified so that they can be integrated into the virtualized testbed so that they can be operated in real time.
Academic Supervisor:
Saioa Arrizabalaga
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Privacy, Code Automation, Containers.
Description and objectives:
Fides is an open source privacy management platform for enforcing privacy standards at the code level. Fides tools allows to tag system privacy features, orchestrate programmatic rights enforcement and audit staff identifiable information stored in all systems and application infrastructures. Fides in turn supports all major privacy regulations (e.g. GDPR, CCPA and LGPD), and standards such as ISO 19944 by default.
This project seeks the automated implementation of the Fides platform in a practical use case, so that a consistent and versioned definition of the privacy features and resources of this system can be created, being used as part of a CI/CD pipeline to process privacy requests.
Academic Supervisor:
Saioa Arrizabalaga
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Security.
Description and objectives:
Monitoring and observability tools are widely used nowadays to have a control of the processes running in our Kubernetes cluster. Most of these tools only provide basic monitoring and observability of the Kubernetes cluster, but few of them apply detection and countermeasure. This scenario makes the ability to monitor the protection of a cluster against attacks very difficult leave. On the other hand, we have tools that offer finding of attacks and alerts, but without applying any countermeasure on it. This project has as goal the development of an alert, finding and countermeasure tool for industrial environments, and the integration of this tool with third party tools, capable of solving the above mentioned problems. These functionalities should be integrated into a custom Kubernetes cluster to monitor and protect the cluster from external attacks.
Academic Supervisor:
Luis Vitores Valcárcel García
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Mathematical Optimization, Data Science
Description and Objectives:
This project has as goal to develop a system that uses Large Language Models (LLMs) to automatically classify sections of a document, which are not complete chapters, but intermediate parts (such as subsections, paragraphs or fragments) of agreement with criteria defined by the Username. For example, the system will be able to identify and classify content sections such as "methodology", "results", "discussion", among others, according to the characteristics of the text.
Through the use of fine-tuning on pre-trained models, the model will be able to label each section according to topics (technology, health, Economics, etc.) or subject of content (informative, argumentative, descriptive, etc.), allowing a more structured organization and analysis of long documents.
Suggested student activities:
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Literature review on text classification, document segmentation and use of LLMs.
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Data preprocessing: Segmentation of documents into sections (not complete chapters) and labeling of data.
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development from model: Fine-tuning of a pre-trained LLM to classify the sections according to the criteria defined by Username.
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Training and evaluation: Evaluate model performance using metrics such as accuracy, recall, and F1-score.
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Implementation of an interface or API: Allow the Username to define the classification criteria and upload documents to classify the sections automatically.
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6. Analysis and improvement of model: Adjust model according to the results obtained, improving classification and accuracy.
Academic Supervisor:
Luis Vitores Valcárcel García
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Mathematical Optimization, Data Science, Environmental Engineering.
Description and objectives:
The use of Generative Adversarial Networks (GANs) in the context of wastewater treatment plants allows the generation of realistic meteorological and influent data from historical time series. These networks can generate synthetic data that simulate actual operating conditions, which facilitates analysis and simulation without the need for constant new data. These generated data can feed reduced order models (ROMs), improving the accuracy of simulations.
In addition, the project can be extended to predict the influent from entrance as a function of meteorological variables, allowing the simulators to be used to optimize plant operation over the following days.
Proposed student activities:
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Literature review on the use of GANs in the generation of data for plant simulation.
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development of a GAN to generate realistic meteorological and influent data.
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Integration of the data generated in plant simulators.
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Extension of model to predict influent from meteorological data.
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Evaluation of results and comparison of the accuracy of the generated models.
Academic Supervisor:
Itxaro Errandonea / Luis Vitores Valcárcel García.
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Artificial Intelligence, Data Science, Machine Learning.
Description and objectives:
Many real industrial processes can be mathematically formulated by complex mechanistic models composed of nonlinear differential equations. Although these models are very useful to carry out studies of design and operation, their handicap is their high computational cost which makes them unfeasible for use in real-time decision making.
With the advent of Deep Learning techniques, proposals have emerged to reduce the complexity of these models and thus the computational cost. The task of this PFG will be to use the technique known as "physics informed neural networks" to obtain a reduced model of a water treatment plant. The Python environment will be used to carry out the project .
Academic Supervisor:
Luis Vitores Valcárcel García
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Mathematical Optimization, Data Science, Environmental Engineering.
Description and objectives:
In wastewater treatment plants in Spain, the volume of incoming and discharged water is recorded daily, generating a continuous database on the influent and effluent of these facilities. To perform simulations and predictions in these plants, mechanistic models based on principles of Biochemistry, thermodynamics and fluid mechanics are used. However, one of the main challenges is that there is no direct correspondence between the available laboratory measurements and the variables needed in the models. This gap prevents accurate calibration of the model, affecting the quality of the simulations.
The project addresses this problem through an influent self-calibration technique, in which the entrance variables in the models are automatically adjusted from the experimental data obtained. This process, similar to a deconvolution, has the goal of improving the accuracy of the simulations and their predictive capability, offering a model adapted to the specific conditions of each plant.
Suggested activities for the student:
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Literature review on self-calibration and deconvolution techniques applied to water treatment plants.
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Mathematical formulation of the influent self-calibration problem.
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Implementation of model in R or Python.
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Analysis of results, evaluating the accuracy and effectiveness of model in specific scenarios.
Academic Supervisor:
Luis Vitores Valcárcel García
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Mathematical Optimization, Data Science
Description and objectives:
The application of time-dependent covariates in survival analysis has improved the prediction of time to default in behavioral credit scoring models. However, when these covariates are endogenous, two problems occur: estimation bias and the lack of a framework to predict the future values of the event and the covariates.
Joint models are a statistical approach that simultaneously integrates longitudinal and survival data, allowing to model the joint evolution of an event of interest (such as time to default) and endogenous time-dependent covariates. This project explores for the first time the application of discrete-time joint models to credit scoring, and proposes a novel extension by including autoregressive terms in the endogenous covariates.
The project will apply these methods to U.S. mortgage data, evaluating whether discrete-time joint models improve predictive accuracy compared to traditional survival models and whether performance is optimized by including an autoregressive term.
Proposed student activities:
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Literature review on conjoint models and their application in credit scoring.
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Mathematical formulation of the model set in discrete time.
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Implementation of model in R or Python.
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Analysis of results, comparing predictive performance against other models.
This project will allow the student to explore advanced statistical modeling techniques applied to financial data and improve predictions in the context of credit risk.
Academic Supervisor:
Luis Vitores Valcárcel García
department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management
area subject:
Mathematical Optimization, Data Science
Description and objectives:
The maintenance scheduling problem, known as the Maintenance Scheduling Problem, consists of optimally organizing maintenance activities within a schedule. This problem seeks to minimize interruptions and operating costs, ensuring that both preventive and corrective maintenance are performed at the right times.
The goal of this end of Degree project is to develop an optimization tool that addresses efficient scheduling of maintenance schedules. The tool will be developed preferably in Python, with additional Matlab or R options.
Proposed student activities:
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Bibliographic review of the most common optimization problems and algorithms applied in maintenance scheduling.
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Mathematical formulation of the problem, establishing the relevant criteria and restrictions.
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Implementation of the solution using a heuristic optimization algorithm or open source solvers.
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Analysis of results and comparison of the effectiveness of the applied approach , with recommendations for its use in different maintenance situations.
Academic Supervisor:
Markos Losada
department Tecnun/Division CEIT:
Transport and Energy Division: Transport and Sustainable Mobility Group.
area subject:
design electronic, coding, data processing
Description and objectives:
The approach of this final work of Degree focuses on the analysis of advanced distance estimation technologies that could be integrated into a system for a wristband to analyze the game of Padel. The project is divided into several phases, starting with a comprehensive analysis of existing commercial systems, evaluating their advantages and proposing improvements. The review of current technologies such as time-of-flight (ToF), Lidar and ultrasound sensors is fundamental to select the most appropriate technology for this purpose. The proposal for improvement will include technology selection, the development of a specific algorithm and system integration, considering factors such as size, cost and power consumption. The goal is for the student to not only gain knowledge about these technologies, but also to propose a concrete solution that can be implemented.
In the implementation phase, the student will be responsible for integrating the selected sensors and developing a system capable of detecting a matrix of points to accurately estimate distances. The results obtained will be analyzed to evaluate the effectiveness of the proposed algorithm and determine the feasibility of its implementation in a commercial product. This project not only seeks to improve the paddle tennis playing experience, but also to explore potential applications of these technologies in other fields, such as weighing or wagon monitoring.
Academic Supervisor:
Iñigo Adín
department Tecnun/Division CEIT:
Transport and Energy Division: Transport and Sustainable Mobility Group.
area subject:
Artificial intelligence learning, coding, data processing.
Description and objectives:
This final work of Degree has as main goal the development and the implementation of machine learning models in low power microcontrollers, specifically of the STM32 family, using TensorFlow Lite. The project focuses on the application of these models in the transportation sector, with a particular approach on the analysis and improvement of automatic braking systems.
To achieve this goal, the student should:
Training in Tools and Technologies:
Acquire knowledge of TensorFlow Lite for microcontrollers, through Machine Learning resources such as Andrew Ng's documentation, and "Machine Learning with Scikit-Learn, Keras and TensorFlow", as a foundation and using Wes McKinney's "Python for the data analysis" as reference letter for management and data analysis.
development of Machine Learning Models:
Design and train machine learning models that can be optimized for execution on low-power microcontrollers.
Evaluate the performance of these models in terms of accuracy, efficiency and energy consumption. For this purpose, data will be collected with a sensorized brake bench and the models will be trained with them.
Integration in Microcontrollers:
Implement the developed models on STM32 microcontrollers using TensorFlow Lite. Ensure that the integration is efficient in terms of resources and reliability of the results.
Application in the Transportation Sector:
Apply integrated models to improve the automatic braking function in vehicles, analyzing real-time data to optimize system safety and efficiency.
Evaluate the impact of the implementation in test scenarios, adjusting the models as needed to improve performance.
The documentation and results will be organized documenting the references and the process of development. The results obtained will be presented, highlighting the improvements achieved in the automatic braking function and possible future applications of the developed technology.
Academic Supervisor:
Emilio Sanchez Tapia
department Tecnun/Division CEIT:
Materials and Manufacturing Division: Robotics and Industrial Control Group.
area thematic:
Robotic Engineering
Description and objectives:
In the context of robotics in the 21st century, the concept of the connected factory arises where machines, mobile robots and humans coexist. Mobile robots may or may not include a robotic manipulator arm or MoMa (MObile MAnipulator). If there is only the mobile robot, it is usually referred to as AMR (Autonomous Mobile Robot) or AGV (Autonomous Guide Vehicle) according to its Degree of freedom in navigation (see figure below).
Figure 1: Constituent elements of a platform-mounted collaborative robot (or MoMa).
The main application of this device subject is to increase the level of factory automation in sectors where today automation has leave penetration, such as intralogistics and machine tending. In these scenarios, the robot can move raw materials, products in the manufacturing process or even search for machine replacement parts (such as a cutting head for a CNC). In any case, the MoMa will be able to perform the task either autonomously or as an assistant to a human operator (see figure below).
Figure 2: Factory scenario where a MoMa becomes one more resource of the factory where it can work alone or in collaboration with other human operators.
A likely scenario is that in the factory we will find more than one mobile robot, each of them with different capabilities and probably from different manufacturers. In this case it is important to have software that coordinates the tasks and distributes them appropriately according to the availability and/or capacity of each robot. Such software is known as a robot fleet manager.
Figure 3: A fleet manager coordinates the work of a set of robots.
There are many fleet management solutions on the market, but they are usually proprietary and compatible with only one brand of robot.
The goal of the final project of Degree is to deploy and test an open-source robotic fleet manager. The tests will be done both in simulation and with real robots.
As of essay of this document, it is planned to use open-rmf (Open-RMF: https://www.open-rmf.org/ ) or equivalent, see the following figure.
Figure 4: Screenshot of a simulation of coordinated fleets from open-rmf.
It is offered, during the execution of project:
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Incorporation to the robotics group of researchers from the CEIT
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Training in the software/hardware tools employed
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Possibility of a job offer in a company in the sector.
Testbeds are fundamental elements for safety testing. However, a first approach is to verify the feasibility of the Testbed based on the development performance test.
The following work aims to create a Testbed for performance testing based on the integration of the digital twin of a Wind Turbine as Hardware In The Loop (HIL), a virtual PLC as OpenPLC and a set of Modbus clients, which will allow scalability testing. The following figure sample shows an architecture of reference letter with the components involved in the Testbed.
Figure 1: Communication flow.
Specifically, the digital wind turbine twin to be integrated is as follows:
Figure 2: Wind generator created on Matlab Simulink.
Figure 3: Attacks on virtual/real PLC.
The project would involve a second approach using a real PLC, i.e., swapping the virtual PLC (OpenPLC) for a real Omron PLC. The rest of the experimentation procedures would be identical. In this way one of the environments could be used as a benchmark to establish a comparison with respect to the other. The tasks to be performed are listed below:
- Analyze the archive base, understanding how to generate information flows.
- Package in a container a wind generator developed in Matlab Simulink (see Figure 2).
- Add the necessary components to establish UDP communication between the simulink model (packaged) and the interfaces (see Figure 1).
- Develop the necessary control code in the virtual PLC to enable communication with the wind turbine.
- Connect the virtual PLC to Modbus clients, created using the bookshop pymodbus, to enable performance testing.
- Collection of performance test metrics for analysis.
- Transform the control code created for the virtual PLC into the code needed for the real PLC to enable communication with the wind turbine.
- Connect the actual PLC to Modbus clients, created using the bookshop pymodbus, to enable performance testing.
- Collection of performance test metrics for analysis.
- Collect tools to exploit existing vulnerabilities on the virtual/real PLC (see Figure 3).
- Performing security tests by classifying them according to the pillar of cybersecurity they compromise, e.g., availability, integrity, etc (see Figure 3).
Testbeds are fundamental elements for security testing. In particular, the field of collaborative robotics constitutes a Safety environment of great interest for cybersecurity research. Progress is currently being made in this direction, working on a flow like the one shown in Figure 1 at sample .
Figure 1: Testbed for cybersecurity testing on collaborative robotics environments.
However, there is still a long way to go in several of these stages. In this paper we intend to study one of them in depth. Specifically, the field device (robot) communication with the IoT Gateway, i.e., the flow shown in Figure 2:
Figure 2: area of Testbed improvement.
1- Since Universal Robots has released a series of simulators, we would be interested to know, which of all is the series or ROBOT_MODEL that would allow us to have greater control over the field device, which translates into greater read/write capability over the device variables.
2- Obtaining and storing records (logs) of the robot as an element core topic for analysis during safety tests. These logs should allow active monitoring of the device.
3- Considering a Raspberry Pi as IoT Gateway, an infrastructure based on K3s will be installed on it. On this K3s infrastructure a microservices based architecture will be deployed which will contain 4 microservices: Modbus client, Kafka Publisher, Kafka consumer, Engine. grade This task will be developed in collaboration with other researchers of the group to carry out an implementation that integrates the CI/CD methodology to enable automatic updates on the Raspberry.
4- A 5G module will be installed on the Raspberry to enable communication with the Amarisoft central. grade This task depends on the purchase process of module.
5- Considering Modbus as the transport protocol between the field device and the IoT Gateway, the following task seeks to improve the code currently generated (packaged in a container) to monitor with certain periodicity the set of variables enabled by the robot.
6- These variables will be collected and sent to a second microservice which uses the protocol Kafka, which should be programmatically optimized to reduce latency and increase throughput. To test this microservice, the test broker exemplified in Figure 3 should be used.
7- A third microservice will be integrated to act as Kafka's publisher, which will also have to be optimized. To test this microservice, the test broker exemplified in Figure 3 should be used.
8- A fourth microservice should be developed to act as a response engine that will depend on the prediction received from the Kafka consumer, based on which it should make decisions that will be transmitted to the Modbus client and transferred to the field device as sample Figure 3.
Figure 3: Integration of Engine on Testbed.
9- Integration of the IoT Gateway on the communication flow of the use case as sample Figure 4. grade This task depends on the progress of other researchers in the group.
Figure 4: Testbed with complete communication flow.
Academic Supervisor:
Ainhoa Rezola
department:
Electrical and Electronic Engineering
Description and objectives:
This project embarks on the cutting edge of technology in collaboration with the Massachusetts Institute of Technology (MIT). It focuses on exploring revolutionary chipless technology for the Internet of Things (IoT), with particular emphasis on frequency coded (FC) chipless tags. These tags, recognized for their economic attractiveness and sensing capabilities, present challenges in terms of sensing and processing.
The proposal involves the use of a device known as Software-Defined Radio (SDR) to carry out measurements and collect data from the tags. The project proposes to apply signal processing techniques with the goal to improve the quality of the information obtained. Also, the potential of Machine Learning (ML) algorithms will be explored to classify more efficiently these tags, thus improving the identification capability.
It is important to note that the reader required for these tasks has already been previously developed, so the main focus will be on the measurement, processing and classification phases. The importance of antennas, fundamental elements in wireless communications, will also be addressed, contributing to the improvement of signal quality and, therefore, to the efficiency of the system.
Academic Supervisor:
Enrique Castaño Carmona
Division CEIT:
Advance Powder Metallurgy and Laser Manufacturing Group
area thematic:
Computing, modeling and simulation
Description and objectives:
The machining of materials using ultra-short pulse lasers is a very recent technology development and opens multiple possibilities in the field of functional surfaces, such as low friction coefficient surfaces in wind turbines or anti-icing surfaces in aeronautics.
Currently, Ceit is leading a European project in which one of its objectives is to develop a simulation software for the machining process with this subject of lasers. The mathematical modeling of the process is already well advanced, as well as its numerical implementation.
The task of this PFG will be to design and develop the graphical interface with the Username of the simulation program so that its use is easy and intuitive. The student will apply and extend his knowledge of Python programming, GUI (Graphic User Interface) and design UX/UI (User Experience/User Interface) to achieve an interface that allows Username an attractive experience of the simulation program.
Academic Supervisor:
Santiago Figueroa Lorenzo
Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Security.
Description and Objectives:
CI/CD is increasingly popular in embedded software development . However, projects are often constrained in a way that they are not in the development of applications (e.g., web). In addition to the physical and computational limitations of the target hardware platform, there are market limitations. The embedded software market has unique requirements security, privacy, and extremely long life cycles (e.g., products can remain on the market for decades). At the level of development, embedded software is not much different than development from typical applications (e.g., web), requiring IDEs, compilers, static and dynamic analysis and dynamics tools. However, the tools typically address architectures on which they work (host vs. target environment). Compiler-level automation uses the same techniques, but when code execution is involved, the host/target barrier becomes significant. Code execution automation requires special support development of software. Software test automation is more challenging due to the complexity of initiating and testing on embedded targets, not to mention the limited limited access to the target hardware that software teams have. This project, aims to carry out a first approach to the basic development CI/CD on embedded systems. Thus, given a basic development in C/C++, it is intended to pass this code through stages of testing, security checks and compilation (CI), to then perform an automated submission on a device (e.g. a microcontroller), but not before also performing functional testing (CD).
Academic Supervisor:
Santiago Figueroa Lorenzo
Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Privacy, Code Automation, Containers.
Description and objectives:
Fides is an open source privacy management platform for enforcing privacy standards at the code level. Fides tools allows to tag system privacy features, orchestrate programmatic rights enforcement and audit staff identifiable information stored in all systems and application infrastructures. Fides in turn supports all major privacy regulations (e.g. GDPR, CCPA and LGPD), and standards such as ISO 19944 by default.
This project seeks the automated implementation of the Fides platform in a practical use case, so that a consistent and versioned definition of the privacy features and resources of this system can be created and used as part of a CI/CD pipeline to process privacy requests.
Academic Supervisor:
Santiago Figueroa Lorenzo
Division CEIT:
ICT Division. Group of data analysis and Information Management
area thematic:
development Software, Security.
Description and objectives:
Monitoring and observability tools are widely used nowadays to have a control of the processes running in our Kubernetes cluster. Most of these tools only provide basic monitoring and observability of the Kubernetes cluster, but few of them apply detection and countermeasure. This scenario makes the ability to monitor the protection of a cluster against attacks very difficult leave. On the other hand, we have tools that offer finding of attacks and alerts, but without applying any countermeasure on it. This project has as goal the development of an alert, finding and countermeasure tool for industrial environments, and the integration of this tool with third party tools, capable of solving the above mentioned problems. These functionalities should be integrated into a custom Kubernetes cluster to monitor and protect the cluster from external attacks.
Academic Supervisor:
Santiago Figueroa Lorenzo
Division CEIT:
ICT Division. Group of data analysis and Information Management
area Thematic:
5G, Kubernetes, Cloud Computing, Virtualization.
Description and Objectives:
The adoption of Cloud Native in 5G telecom systems has been identified as a good candidate to reduce cost, improve system agility and the role of 5G services. Based on the 3GPP standard, the European Telecommunications Standards Institute (ETSI) has published the reference letter architecture of NFV tailored to Cloud Native environments and to enhance the framework of NFV, including, containers, load balancers and other elements as part of the architecture of reference letter.
This work pursues the validation of container technology on the MANO platform hosted at ETSI, in a CN environment, so that the results obtained in the work can help to encourage users and operators to use KNFs and thus taking advantage of container technologies.
Academic Supervisor:
Paul Zabalegui
Division CEIT:
Transportation and sustainable mobility
area subject:
Telecommunication engineering
Description and objectives:
The use of positioning systems is becoming more and more common in the daily life of both people and companies, which integrate them in their systems as core topic pieces when it comes to want a safety and efficiency Degree that meets market expectations. In this sense, the major players in the railway sector (CAF, Thales, SNCF, Siemens, etc.) are devoting great efforts to the precise and continuous positioning of their trains.
As its positioning systems are mainly based on GPS/GNSS technologies, the main challenge for challenge is to locate the receivers in indoor environments, where the satellite signal is degraded. Currently, Ceit is involved in a major European initiative that seeks to develop total positioning systems that work both indoors and outdoors, and that do so accurately and continuously, in order to reach the highest level of maturity on the road to the autonomous train Degree .
The task of this PFG would be to design and implement a WiFi-based positioning system that operates indoors and can be further merged with GPS/GNSS technologies.
Academic Supervisor:
Paul Zabalegui
Division CEIT:
Transportation and sustainable mobility
area subject:
Telecommunication engineering
Description and objectives:
The use of positioning systems is becoming more and more common in the daily life of both people and companies, which integrate them in their systems as core topic pieces when it comes to want a safety and efficiency Degree that meets market expectations. In this sense, the major players in the railway sector (CAF, Thales, SNCF, Siemens, etc.) are devoting great efforts to the precise and continuous positioning of their trains.
As its positioning systems are mainly based on GPS/GNSS technologies, the main challenge for challenge is to locate the receivers in indoor environments, where the satellite signal is degraded. Currently, Ceit is involved in a major European initiative that seeks to develop total positioning systems that work both indoors and outdoors, and that do so accurately and continuously, in order to reach the highest level of maturity on the road to the autonomous train Degree .
The task of this PFG would be to conduct a study of the use of 5G technology for indoor positioning and to implement a 5G-based positioning algorithm that makes use of synthetic signals simulated using Matlab.
Academic Supervisor:
Paul Zabalegui
Division CEIT:
Transportation and sustainable mobility
area subject:
Telecommunication engineering
Description and objectives:
The use of positioning systems is becoming more and more common in the daily life of both people and companies, which integrate them in their systems as core topic pieces when it comes to want a safety and efficiency Degree that meets market expectations. In this sense, the major players in the railway sector (CAF, Thales, SNCF, Siemens, etc.) are devoting great efforts to the precise and continuous positioning of their trains.
As its positioning systems are mainly based on GPS/GNSS technologies, a major challenge for challenge is to obtain continuous centimeter accuracies on a global basis. Currently, Ceit is involved in a major European initiative to develop total positioning systems that are capable of locating trains ultra-precisely on their mission statement along the tracks, in order to reach the highest Degree of maturity on the road to the autonomous train.
The task of this GFP would be to implement an algorithm for decoding HAS augmentation signals from Galileo satellites for ultra-precise positioning, and its application to an already functional Matlab positioning algorithm based on GPS/GNSS signals.
Academic Supervisor:
Yuemin Ding
department Tecnun:
Electrical and Electronic Engineering
area thematic:
Telecommunication
Description and objectives:
Online monitoring and data collection in ultra-remote areas is specifically meaningful to investigate the local characteristics of climate change, biodiversity evolution, etc. It is also very important to prevent huge disasters, such as wildfires. However, online monitoring and data collection in ultra-remote areas have been challenging during the past decades. A major challenge is the lack of digital infrastructure for communication and data collection. However, the emerging satellite networking (such as Starlink) and low-power and long-distance IoT (such as MIoTy) technologies enable an alternate solution for online monitoring and data collection. The aim of this project is to develop a system based on satellite networks and low-power and long-distance IoT to enable online monitoring and data collection in ultra-remote areas.
Academic supervisor:
Íñigo Adín
Division CEIT:
ICT Division
area thematic:
IoT, communications, low power, Bluetooth.
Description and objectives:
This project proposes the evaluation of Bluetooth 5.1 technology in its modality Long Range for use in industrial environments. The aim here is to see the possibilities of this longer range version to compete in IoT technologies to be installed in production plants or in remote sensors, with range for the admissible meters in this case.
The aim is to evaluate this technology using evaluation boards and configuring the elements at FW and SW level to measure the signal quality in parameters potentially useful in industrial applications (time of flight, data rate, packet error rate, etc.). To do this, a search for these evaluation boards will be proposed and programming will be required using the admissible interfaces in each case.
Academic supervisor:
Leticia Zamora Cadenas - Iker Aguinaga Hoyos.
Division CEIT:
Information and Communication Technologies. Intelligent Systems for Industry 4.0 Group.
area thematic:
Telecommunication/Industrial Engineering
Description and objectives:
Indoor location systems are a booming element in recent years. Whether using radiofrequency technologies, inertial sensors or artificial vision systems, the location of objects or people in interior spaces is an element core topic in many applications (tracking of parts, access to security areas, tracking of people, augmented reality, etc.).
To determine and evaluate the accuracy of a location system, the most common method is to measure guide a number of control points or tests in a controlled environment to determine the accuracy of the system. However, this subject measurement is always subject to measurement errors, human error, and the impossibility of tracking a moving element in real time. Another widespread option, especially when the accuracy is to be evaluated dynamically, is to resort to cost-effective systems that allow the creation of the real path or "ground truth", such as, for example, vision tracking systems. However, it is not always possible to deploy this type of system subject , or the economic means to do so are not always available. Therefore, being able to evaluate the accuracy of indoor positioning systems at a low cost is still a problem that researchers and companies are trying to solve.
Currently Ceit has a line of research associated with positioning systems for indoor spaces, in which it works with various companies to provide solutions to their needs. This is why the need for a ground truth system that is easy to install and not too expensive was born.
The task of this GFP would be to develop a ground truth system, using virtual/augmented reality systems, for subsequent use in evaluating the accuracy of the proprietary indoor location system Ceit. HTC Vice, Oculus Quest and Hololens 2 hardware are available for the development of this system using the Unity3D programming platform. The candidate must have programming skills in C# or similar languages such as C++ or Java.
Academic supervisor:
Emilio Sánchez Tapia
Division CEIT:
Information and communications technologies. Intelligent Systems for Industry 4.0 Group. Vision and Robotics Subgroup
area thematic:
Robotics Engineering
Description and objectives:
Industry 4.0 has paved the way for multiple forms of automation that have as goal improve productivity and optimize work processes. In this context, the aim is to develop an intelligent mobile manipulator: a new robot subject that integrates the technology of an autonomous mobile robot and a highly efficient collaborative robotic arm capable of performing various operations.
The idea of project is to develop a robot that can move, detect and avoid obstacles, explore its environment to recognize objects through artificial vision and perform part handling tasks, being able to interact with operators. With the idea of implementing a digital transformation model , required today in real factory environments, robots, control elements, sensors and other onboard elements will be connected to each other through a digital platform to control the process in real time and from anywhere.
Currently CEIT has already developed a first working prototype (see figure below).
The task of this GFP would be the programming under ROS-2 of a sequence of tasks for the robot to interact with a classic robotic cell. The specific case to be developed will be for the robot to go to a archive of parts to be processed, bring them to the cell, wait for their processing and take them to another storeroom of already sorted parts.
Under this simple task, the concepts of:
- Collaborative mobile robotics
- Machine tending
- Control in force
- Problem of synchronisation of two automatic devices
Programming skills in C/C++, Python or java-script are required.
Academic supervisor:
Diego Borro
Division CEIT:
Intelligent Systems for Industry 4.0
area thematic:
Telecommunication Systems Engineering
Description and objectives:
Copernicus is the world's largest Earth observation programme to date. The programme is a joint initiative of the European Commission and the European Space Agency (ESA) to build an autonomous Earth observation system. The Copernicus programme relies on a family of satellites called Sentinel, owned by the European Union and developed to meet the needs of the Copernicus services and their users.
Every object on the Earth's surface reflects and absorbs energy in a variety of ways. The spectral signature represents the unique way in which a surface reflects the sun's energy, within the electromagnetic spectrum. In addition, spectral signatures are typically characterized on an X-axis (wavelength) and Y-axis (percent reflectance) graph so that different surfaces have different spectral signatures.
Currently there are a multitude of data, tools and software,... to access and process satellite data. The goal of this PFG would be to access multispectral information from a certain area of the planet and process it to obtain certain information such as changes in land cover, algae growth in the water, different types of crops, or the amount of urban development in a area. The specific information needed depends on the application and will be defined when the PFG starts.
The student will not start from scratch as a PFM has been defended and has made a study of the art of all existing technologies and tools.