New technologies in photovoltaic generation, stationary storage, and energy management for distributed generation under the paradigm of energy communities – Modelling of Redox Flow Batteries with Organic Electrolytes
Digital Twin for a photovoltaic solar power plant, both to diagnose the state of health of the plant and supply maintenance recommendations, to reduce costs, extend lifetime, and achieve a better return on investment
High-power, high-frequency power converters for heavy-duty long-haul electric vehicles to obtain improved performance, safety, reliability, cost and sustainability
Digital Twins and applied IoT with advanced cloud-based functionalities for the management of energy, infrastructures and assets of intensive industries in urban environments
Digital Twins for Li-ion batteries, to improve operation, efficiency and lifetime, and advanced physic and data-driven models for battery diagnosis and prognosis
New concept of a smart, modular and scalable battery pack for a wide range of electric vehicles used in urban electromobility services, from mid-size electric vehicles to electric buses
Development and validation of the first 5 kW all-copper redox flow battery prototype for stationary storage applications, achieving sustainability, cost and performance using a new material, an innovative design, and intelligent control
Low-cost system for energy control in the SOHO segment, making the user a central element in decision-making, and using AI to obtain a reduction in energy consumption
Improvement of the quality of mental health in young people management and ensure affordable services by sharing information, providing scalable digital tools, and ensuring personalized decision-making and evidence-based interventions in an effective way
A comprehensive CAD system based on radiologic- and pathologic-image biomarkers for diagnosis and prognosis of breast cancer relapse for distant metastasis
Creation of trainable knowledge models that benefit from a personalised and precise integration of air quality data acquisition with the real-time evolution of physiological parameters in the development of several breathing disorders
Effects of the daily exposition to some prevalent atmospheric pollutants on patients with COVID-19 and other high-risk respiratory diseases, such as COPD and asthma
Cutting-edge unobtrusive sensing technologies and advanced AI techniques to create a health monitoring system enabling early prediction of Diabetes Mellitus, Congestive Heart Failure and related diseases
Monitoring of Activities of Daily Living (ADL) of elders living alone at home, using gas sensors and applied AI to design identification algorithms through ML techniques
Use of graphene sensor networks in Ambient Assisted Livings environment to detect human activities, and integration into a monitoring system to feed AI and decision support algorithms
Cutting-edge quantum sensing, edge continuum orchestration of AI and distributed collaborative intelligence technologies to implement the vision of intelligent and autonomous electronic components and systems in the digital
Building intelligent Management System, based on edge computing and explainable AI, that will be designed and validated by conducting a pilot test in a real environment. Estimates and predictions will be recommended to users following a social computing approach, maximizing indoor comfort, and adapting to changing patterns.
Development of new chemoresistive gas sensors with enhanced stability, selectivity and ultralow power consumption, with improved data acquisition through edge- and cloud-based AI algorithms, implementing data prediction strategies to handle missing data
Non-invasive methodology for the diagnosis of leishmaniasis in dogs via the analysis of volatile breath samples, employing analytical methods and a system composed of different chemical gas sensing devices
Continuous and real-time monitoring of Volatile Organic Components (VOCs) produced by meat inside a refrigerator using gas sensors to be aware of its freshness and quality
Gas sensing enhanced with edge computing powered by a microprocessor based on a RISC-V architecture, and optimized for low energy consumption and high data security
Monitoring of Activities of Daily Living (ADL) of elders living alone at home, using gas sensors and applied AI to design identification algorithms through ML techniques
Use of graphene sensor networks in Ambient Assisted Living environments to detect human activities, and integration into a monitoring system to feed AI and decision support algorithms
Design, development and validation of an innovative prototype of a graphene-related node for a wireless sensor network to be used as autonomous system for environmental monitoring on different areas