Design of platforms based on blockchain technology applied to different use cases

[EN]The developments of my PhD in this past year are shown in this article. It is studied thoroughly the possibilities and limits of the blockchain protocols when used in IoT platforms. It is commented how the scalability limits of blockchain technology affects the performance of the systems that make use of it. Also, a review of the state of the art has been carried out, pointing out how some solutions make use of a centralization process to improve response time and security of the blockchain. As future remarks, it should be studying the possibility of creating a public blockchain network with the IoT devices of the platform

Hacia un Diseño Flipped-Classroom para Asignaturas de Diseño y Sistemas de Bases De Datos con Perspectiva Multidisciplinar en el Proceso Comunicativo

Memoria ID-2020/005 Ayudas de la Universidad de Salamanca para la innovación docente, curso 2020-2021

El APS y la tercera misión de la Universidad en las asignaturas de edición digital multimedia

Memoria ID2022-101. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2022-2023

El aprendizaje servicio desde la base de la informática

Memoria ID-062 Ayudas de la Universidad de Salamanca para la innovación docente, curso 2020-2021

Plataforma inteligente para la evaluación del rendimiento académico

Memoria ID-086. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2019-2020.[ES]El objetivo principal del proyecto es diseñar una plataforma en la que se pueda observar y medir la evolución del rendimiento académico a partir de datos tanto encuestados como relativos al desarrollo de la asignatura, para la extracción de conclusiones sobre los factores que determinan dicho rendimient

Aplicación móvil para la corrección automática de tests y encuestas con visión artificial

Memoria ID-197. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2018-2019

A Framework for Knowledge Discovery from Wireless Sensor Networks in Rural Environments: A Crop Irrigation Systems Case Study

This paper presents the design and development of an innovative multiagent system based on virtual organizations. The multiagent system manages information from wireless sensor networks for knowledge discovery and decision making in rural environments. The multiagent system has been built over the cloud computing paradigm to provide better flexibility and higher scalability for handling both small- and large-scale projects. The development of wireless sensor network technology has allowed for its extension and application to the rural environment, where the lives of the people interacting with the environment can be improved. The use of “smart” technologies can also improve the efficiency and effectiveness of rural systems. The proposed multiagent system allows us to analyse data collected by sensors for decision making in activities carried out in a rural setting, thus, guaranteeing the best performance in the ecosystem. Since water is a scarce natural resource that should not be wasted, a case study was conducted in an agricultural environment to test the proposed system’s performance in optimizing the irrigation system in corn crops. The architecture collects information about the terrain and the climatic conditions through a wireless sensor network deployed in the crops. This way, the architecture can learn about the needs of the crop and make efficient irrigation decisions. The obtained results are very promising when compared to a traditional automatic irrigation system

Towards a Blockchain-Based Peer-to-Peer Energy Marketplace

Blockchain technology is used as a distributed ledger to store and secure data and perform transactions between entities in smart grids. This paper proposes a platform based on blockchain technology and the multi-agent system paradigm to allow for the creation of an automated peer-to-peer electricity market in micro-grids. The use of a permissioned blockchain network has multiple benefits as it reduces transaction costs and enables micro-transactions. Moreover, an improvement in security is obtained, eliminating the single point of failure in the control and management of the platform along with creating the possibility to trace back the actions of the participants and a mechanism of identification. Furthermore, it provides the opportunity to create a decentralized and democratic energy market while complying with the current legislation and regulations on user privacy and data protection by incorporating Zero-Knowledge Proof protocols and ring signatures

A Genetic Programming Strategy to Induce Logical Rules for Clinical Data Analysis

This paper proposes a machine learning approach dealing with genetic programming to build classifiers through logical rule induction. In this context, we define and test a set of mutation operators across from different clinical datasets to improve the performance of the proposal for each dataset. The use of genetic programming for rule induction has generated interesting results in machine learning problems. Hence, genetic programming represents a flexible and powerful evolutionary technique for automatic generation of classifiers. Since logical rules disclose knowledge from the analyzed data, we use such knowledge to interpret the results and filter the most important features from clinical data as a process of knowledge discovery. The ultimate goal of this proposal is to provide the experts in the data domain with prior knowledge (as a guide) about the structure of the data and the rules found for each class, especially to track dichotomies and inequality. The results reached by our proposal on the involved datasets have been very promising when used in classification tasks and compared with other methods