Smart Grids (SG) are a result of the progressive application of information and telecommunication technologies to traditional electrical grids. SG services enable the introduction of grid edge technologies, resulting in a changing energy production and delivery model, with greater control and involvement by customers. SG services are both a desire and a must towards grid sustainability and efficiency.
Smart Cities are living environments where sensors are used with different purposes: security, traffic control, efficient energy consumption, smart provision of services, etc. In the near future, these sensors will be connected to the Internet, and interconnected among them, creating heterogeneous Smart Sensor Networks. The aim of these networks is to monitor the environment, to collect information, and to use this information to plan the provisión of services, such as security, cleaning services, traffic arrangement, and to guarantee quality of living, for example, warning for sound pollution or environmental noise, air pollution, etc. The implementation of array processing algorithms to determine the source of information will be also studied. This research line aims at: 1) Studying different alternatives to create heterogeneous smart sensor networks; 2) Developing signal processing algorithms for data fusion, coverage estimation, information source localisation and tracking; 3) Using the obtained information to improve services provision. One of the main objectives is to improve the quality of life in our cities, and to optimise energy consumption when providing these services.
Synthetic Aperture Radar (SAR) systems are powerful Earth Observation (EO) tools that can be used for marine safety, monitoring the traffic, trying to prevent illegal, unreported and unregulated fishing, supporting search and rescue tasks and for oil spill pollution surveillance. SAR systems produce high-resolution imagery of wide areas under any weather condition, and during day and night. However, automatic interpretation of SAR images is very difficult taking into consideration SAR speckle noise and the complex marine environment and the wind conditions. Research areas: estimation of sea surface wind speed and wind direction from SAR data; classification of oil spills using the external data provided by the wind conditions and vessel detection; design of processing architectures fulfilling the near-real-time requirements.
Passive radars, an emerging green technology for traffic (aerial, ground and maritime) monitoring and critical infrastructure protection
Passive Radars (PRs) are defined as a set of techniques whose main objective is to detect targets and to estimate parameters using non-cooperative signals (such as broadcast, communications, radar, or radio-navigation signals) as Illuminators of Opportunity (IoO), rather than using a dedicated radar transmitter. As a result, they overcome all active radar drawbacks associated to the use of a dedicated transmitter. On the other hand, commercial off-the-shelf (COTS) devices can be used for signal reception (antenna, RF front-end and acquisition systems). Research areas: improved digital array signal processing techniques for 3D-detection and tracking of targets in PRs with moving IoOs (on satellites), moving PR receivers (on aircrafts); data fusion in multistatic configurations: several IoOs, several PR receivers or both; design of new antenna solutions for generating multiple narrow beams capable of fulfilling design requirements imposed by PRs exploiting GPS and Digital Video Broadcasting- Satellite (DVB-S) illuminators.
The main research line of the group is Machine Learning approaches for analyzing and designing Renewable Energy systems, including Wind, Solar and Marine Energy Systems.
One significant line of research of the group focuses on micro-grid (MG) design and optimization problems in smart grids using meta-heuristics and Machine Learning approaches. We are also interested in the application of novel soft computing techniques to smart grids challenges.
The main target of this research project is to deploy robust solutions for automatic activity detection in extended videos. Typically, an advanced intelligent transportation system needs to work with long videos, that normally arrive in an online fashion. These extended videos contain significant spans without any activities and intervals with potentially multiple concurrent fine grained activities. Therefore, it results fundamental to research on novel online methods for the task of activity detection and to implement solutions for the problem of concurrent fine-grained activity detection. This fine-grained capability will play a fundamental role to envision the new era of smart transportation solutions, where the artificial intelligent agents will be able to interact and interpret the environment in a fine-grained fashion, hence extracting more semantic information.
The main objective of this line of research is to apply the most advanced techniques in artificial intelligence and computer vision to address the development of new intelligent transport and mobility solutions. In particular, we will address the problem of advanced vehicle detection and counting approaches for the problems of: a) smart routing; and b) prediction and management of traffic congestions;
Power line communication (PLC) systems are becoming a mature field with an increasing scientific and industrial interest. PLC provides broadband connection by using the existing mains, easing the connection of different devices. The medium access techniques recommended in the standards of PLC are OFDM, with and without a window in the transmitter, and Wavelet OFDM, based on a cosine modulated filter bank. Indoor positioning systems (IPS) provide a position fix for devices inside different buildings. Their use and applications have increasing scopes ranging from context data assisting/forwarding in museums, object tracking, marketing, etc. A common approach for IPS, is to deploy radio-frequency beacons inside the building and have a tag that collects the signals from those beacons to obtain the position fix. For achieving our goals, specific communication channel models, machine learning, pattern recognition and signal processing techniques are necessary. Therefore, investigation effort is necessary to understand, propose and develop the relevant methods, algorithms and techniques that may impulse the envisioned scenario.
Smart Grid (SG) and Internet of Things (IoT) will mark one of the greatest technological changes of the first half of the 21st century. In both scenarios, the use of communication technologies must provide capacity, efficiency and reliability in the transmission of information. In addition, it is important to impose the cost of these technologies as a criterion of choice, since their deployment must not involve an economic effort that would lead to the delay or abandonment of their implementation. This research line focuses on power line communications applied to the abovementioned fields, analysing problems involved in broadband PLC for in-home and vehicular applications, as well as narrowband communications within the Smart Grid framework. For the previous medium access technologies, we are looking for candidates with experience in new techniques of time synchronization, channel estimation, time domain or frequency domain equalization, among other issues.