In indoor scenarios, such as meeting rooms, exhibitions, museums or, even, homes, a huge demand on communications and location-based services (LBS) is expected in near future, mainly motivated by the emerge of the Internet of Things (IoT) era. One of the technologies called to play an important role is the one based on visible light, that is leveraged on the technological advances in Light Emitting Diodes (LED).
LED devices have evolved steadily in recent times, so in addition to lighting allow other interesting applications. For example, one of the most important objectives is to reach complete and cheaper communication through them. Currently this is known as lifi, and some prototypes perform this functionality. the LiFi communication can come to play an importat rol to different market as the automotive sector, users position inside of buildings, industry 4.0, etc. This proposal aims to develop communication and positioning systems to several sectors of industry, transport, etc..
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.
This research topic addresses the configuration and study of low power system-on-chip (SoC) used in embedded systems where the autonomy is a key factor of success for the validity of any commercial project. We have experience in the research of FPGAs and system on chip modules based on Xilinx Zynq. The project might provide a common framework to compare the power consumption of embedded system and offering end-users with debugging capabilities to know where to put the efforts while designing for a low-power programable system on a SoC module.
This research topic addresses the deployment of wearable sensors that together with fixed nodes might be used in advanced energy management. We have experience in the application of hybrid systems for in indoor localization of people in smart buildings. The fixed IoT nodes provide an accurate positioning information and can be used as routers for uploading information to the cloud. Simulation of edge-devices plus the indoor localization techniques in IoT motes for a large deployment inside a smart building might be considered valuable.
Efficient Shared of Green Energy Consumption on Smart Buildings
This research topic addresses the deployment of IoT nodes on a smart building equipped with a shared renewable photovoltaic generation system. Collaborative economy and shared resources are in the background of this research line. Each flat owner will have IoT fixed nodes at the main consumer devices, requesting its service when best available. A credit system for each community should be envisaged so both the shared of green energy and efficiency are considered when connecting the devices. The IoT deployment shall be capable to control the electricity consumed by the equipments choosing the best time to be switched on lowering the electricity demand while maximizing the consumption of all the available generated green electricity. The goal is to match the generation of the photovoltaic system (green energy) with the demand so the community takes advantage of the whole green electricity generation. The IoT network would keep track of the delayed requests done by users, switching on the equipments based on a smart schedule, while reporting to everyone their consumption so the people behaviour could be changed to better use the energy.
Smart energy management system for Secure HANs (Home Area Networks) that integrates with Smart grid architectures
Energy management system that integrates Smart Grids with Home Area Networks (HAN) that use smart appliance, home automation and Internet of Thing devices must address security and privacy features. That system must enable energy efficiency, energy service demand and save energy through monitoring and controlling energy in real time.
Computer Vision algorithms are a key element in order to make smart cities, transportation and mobility a reality. Our research interest are in Computer Vision in general and in efficient (low computational resources and real time) object detection and tracking in particular, with special interest in face analysis, which can applied in different problems related to smart mobility and smart cities.
Our main research lines comprise coordination mechanisms and services for the efficient use of shared limited resources. We frequently apply them to environments with autonomous stakeholders where, besides efficiency, different types of fairness and “social welfare” as well as all sorts of “security” constraints need to be considered, so as to enable an effective implementation. For this purpose, we usually combine multiagent techniques from a sandbox that we call “agreement technologies” (semantic technologies, market-based mechanisms, automated negotiation and argumentation, trust and reputation, norms and organisations, …). The ultimate goal is to provide innovative new services to the user, and at the same time to reduce CO2 emissions and energy consumption.