Dynamic ventilation certificate for smart universities using artificial intelligence techniques.

The issue of room ventilation has recently gained momentum due to the COVID-19 pandemic. Ventilation is in fact of particular relevance in educational environments. Smart University platforms, today widespread, are a good starting point to offer control services of different relevant indicators in universities. This study advances a Ventilation Quality Certificate (VQC) for Smart Universities. The certificate informs the university community of the ventilation status of its buildings and premises. It also supports senior management's decision-making, because it allows assessing preventive measures and actions taken. The VQC algorithm models the adequacy of classroom ventilation according to the number of persons present. The input used is the organisation's existing data relating to CO2 concentration and number of room occupants. AI techniques, specifically Artificial Neural Networks (ANN), were employed to determine the relationship between the different data sources included. A prototype of value-added services was developed for the Smart University platform of the University of Alicante, which allowed to implement the resulting models, together with the VQC. The prototype is currently being replicated in other universities. The case study allowed us to validate the VQC, demonstrating both its usefulness and the advantage of using pre-existing university services and resources.

Hardware design of the cortical-diencephalic centre of the lower urinary tract neuroregulator system.

The neuroregulator system in humans controls organ and system functioning. This system comprises a set of neural centres that are distributed along the spinal cord and act independently together with their nerve interconnections. The centres involved in this task were isolated in previous studies through investigations of the functioning and composition of the neuroregulator system of the lower urinary tract to elucidate their individual performances and enable the creation of a general neuroregulator system model capable of operating at the neuronal level. Although the long-term goal of our research is the development of a system on chip (SoC) capable of behaving as a fully programmable neuroregulator system, this work is another step in which we test the viability of the hardware design of one of these neuroregulator centres (specifically the cortical-diencephalic centre) to achieve a first prototype and architectural proposal. To this end, the behaviour of this centre has been isolated, a hardware design implemented on FPGA has been proposed to create a prototype, a simulation environment has been built for the evaluation, and finally, the results have been analysed. This system verified that the functional behaviour corresponded to the expected behaviour in humans and that the operational requirements for the implementation were technically and architecturally viable.

SOA-based model for value-added ITS services delivery.

Integration is currently a key factor in intelligent transportation systems (ITS), especially because of the ever increasing service demands originating from the ITS industry and ITS users. The current ITS landscape is made up of multiple technologies that are tightly coupled, and its interoperability is extremely low, which limits ITS services generation. Given this fact, novel information technologies (IT) based on the service-oriented architecture (SOA) paradigm have begun to introduce new ways to address this problem. The SOA paradigm allows the construction of loosely coupled distributed systems that can help to integrate the heterogeneous systems that are part of ITS. In this paper, we focus on developing an SOA-based model for integrating information technologies (IT) into ITS to achieve ITS service delivery. To develop our model, the ITS technologies and services involved were identified, catalogued, and decoupled. In doing so, we applied our SOA-based model to integrate all of the ITS technologies and services, ranging from the lowest-level technical components, such as roadside unit as a service (RSUAAS), to the most abstract ITS services that will be offered to ITS users (value-added services). To validate our model, a functionality case study that included all of the components of our model was designed.