A selection of R&D&I projects and contracts that are currently being carried out within CETINIA are detailed below:


The main goal of ABACO (Automatic Bed Assistance based on Continuous Optimization) project — developed in collaboration with Pixelabs S.L — is to develop, by using techniques and methods of Data Science, an intelligent algorithm that is able to learn dynamically by using several sleep session reports from smart-mattress and find optimal-pressures patters depending on the characteristics of the user. Thus, it is possible to know which parameters need to be changed to improve the experience, the comfort, and the quality of the sleep.

Executing unit: DSLab


The need for sustainable agriculture has led to the recent introduction of agriculture mobile robots and precision agriculture that makes the practice of farming more accurate and efficient. So far, research has focused mainly on single robots and their agriculture-specific capabilities. The AGROBOTS project will develop smart models and algorithms for scalable, efficient, and decentralized coordination of automated agricultural vehicle fleets.

Executing unit: GIA


CS Track is a H2020 RIA project aimed at broadening our knowledge about Citizen Science and the impact Citizen Science activities can have. CS Track will do this by investigating a large and diverse set of Citizen Science activities, disseminating good practices and formulating knowledge-based policy recommendations in order to maximise the potential benefit of Citizen Science activities on individual citizens, organisations, and society at large.

Executing unit: LITE


DRACO (Dynamic Recover and Automatic Communities Organizer) is a project that will provide a software tool capable of dynamically modeling social behavior and automatically detect the communities in which individuals are organized according to their behavior. For this purpose, techniques for the recovery and organization of information, Data Science and Machine Learning will be used.

Executing unit: DSLab


The e-Madrid-CM project is a research network supported by the Regional Government of Madrid. Its research lines and objectives are aligned with short- and long-term priority themes for computers in education, including Smart learning environments and AI, or Serious games, Gamification and Simulations.

Executing unit: LITE


EMOBRAND (System for the Visualization of Brand Emotion from Multiple Views) is a tool able to evaluate and provide a visualization about the image of a brand on the network, as well as the relation of the image with the brand identity. Techniques for the recovery and organization of information, Data Science, Machine Learning, Artificial Intelligence, Text Processing and Computer Vision will be used.

Executing unit: DSLab


Internet of Things (IoT) to preserve intensive livestock. This project is coordinated by the Union of Small Farmers (UPA). The objective is to prevent wolf attacks by analyzing online data from livestock farms. These data are collected using digital cowbells -developed by Digitanimal- that allow the positioning and monitoring of the animals to be followed.

Executing unit: DSLab


The InEDGEMobility project aims at novel ICT services that facilitate the transition to a more sustainable and individual-centered mobility model. The proposal focuses on (i) adaptive and efficient online coordination of infrastructure resources (ii) dynamic prioritization in the use of transportation infrastructure resources (iii) collaborative bottom-up sharing of transportation resources. Using techniques from the field of Multiagent Systems, Agreement Technologies, Block Chain, Machine Learning, and several others, a proposal for an integrated solution will be developed, as well as techniques, methods and tools to proceed in this direction.

Executing unit: GIA


Design and implementation of a tool capable of evaluating the reputation of digital content on the web, which will detect fraudulent content through the application of Data Science techniques, Big Data architectures and Artificial Intelligence (Deep Learning and Intelligent Agents). SABERMED will incorporate data consolidation techniques, pattern recognition, intelligent agents, decision support, information visualization and representation, as well as advanced Big Data architectures that maximize system efficiency by optimizing the infrastructure and its associated resources.

Executing unit: DSLab

A complete list of active projects and information on completed projects can be found on the respective websites of CETINIA's research groups.