The Instituto Valenciano de Investigaciones Agrarias (IVIA) is a public research Institution with large experience in agricultural research and technological transfer services. More than 400 people work in it. IVIA collaborates with the Spanish and Regional Governments through the agricultural research programs that are regarded as national priority by the Ministry of Agriculture, the National (INIA) and the regional Research Agency. The group started at IVIA working in machine vision for the agriculture at the end of 80’, developing vision systems for robotics aimed at automating agricultural labours, including the software development. Since then, the group has participated in numerous national and international projects, and others funded by the local government or companies, achieving several patents and having active collaboration with national and international research groups. The goals are: to increase and ensure the quality of food products through the automatic control and inspection of production processes, to increase the safety of the food chain to improve the traceability of agro-industrial processes and to automate agricultural tasks by developing novel technology based on computer vision. More recently, their IT programming skills include the development of software and applications for mobile devices.
Nowadays, technology is present in every aspect of our lives, however, it is necessary to understand and analyze human activity if we want to fit technologies into people’s everyday lives. The activity in its various facets and develops innovative and radical forms of human-computer interaction to ensure that technology is integrated naturally and seamlessly in our daily activities. From a scientific point of view, our interest are to understand and classify the relevant significance of each aspect of the human activity and how to use this information in computer mediated technologies for enhancing human abilities and quality of life. From a technological point of view, our objectives are to improve interactive technologies like mixed realities, natural user interfaces and /or smart mobile devices used at different formats and the development of algorithms, methods and techniques for ubiquitous and non-obtrusive measurement of human activity. We are particularly interested in applications which augment a people’s abilities in the areas of health, learning, collaboration and decision-making.
CUINA conducts its research at Universitat Politècnica de València focused in the field of Food Technology, trying to solve problems to the food industry related to the food processing and preservation. From the basis given by a fundamental analysis of all the factors involved we aim to contribute to satisfy the current consumer demand for safe and high quality products.
The Multivariate Statistical Engineering Group (MSERG) was set up in 2004 with the aim of providing the scientific community and the business world with a working environment in which to undertake research in the sphere of multivariate statistical techniques applied to improving the quality and productivity of processes. Several of the researchers in the group have lengthy experience in the discipline of multivariate statistical process control, (monitoring, fault detection & diagnosis, and predictive models), multivariate image analysis, and Six Sigma methodology for process improvement. The group has developed its lines of research in various scientific fields that have experienced a breakthrough in the last decade: Multivariate Statistical Process Control (MSPC), Multivariate Image Analysis (MIA), “omic” sciences, N-way methods, Olfactory Sensometrics, or the recent Systems Biology.
Nowadays there has been an enormous increase in the amount of available data sets of any kind. As a result, the need of applying techniques to analyze and extract information of those data has become a crucial task. The intelligent analysis of data opens a new way of addressing problems impossible to deal with so far. IDAL is concerned with the application of techniques coming from very different areas such as statistics, artificial intelligence, data mining, computational statistics, machine learning, optimization, dynamic programming; to real-world data analysis problems. The IDAL has successfully applied those techniques to a wide range of applications in Medicine (Cardiology, Urology, Radiology, Intern Medicine, etc), Pharmacy (Pharmacokinetics, Pharmacodynamics, reinforcement learning in dosage optimization) intelligent processing of biomedical signals, models of prediction in environment, Web mining, marketing, etc.