Recommender systems based on hybrid models

[EN]Recommender Systems (RSs) play a very important role in web navigation, ensuring that the users easily find the information they are looking for. Today’s social networks contain a large amount of information and it is necessary that they employ mechanism that will guide users to the information they are interested in. However, to be able to recommend content according to user preferences, it is necessary to analyse their profiles and determine their preferences. The present study presents the work related to different recommender systems focused on two different hybrid models. Both of them are using a Case-Based Reasoning (CBR) system combined with the training of an Artificial Intelligence (AI) algorithm. First, some information is analyzed and trained with an AI algorithm in order to determine relevant patters hidden on the information. Then, the CBR system extends the system using a series of metrics and similar past cases to decide whether the recommendation is likely to be recommended to a user. Finally, the last step on the CBR is to propose recommendations to the final user, whose job is to validate or reject the proposal feeding the cases database

The role of Artificial Intelligence and distributed computing in IoT applications

[EN]The exchange of ideas between scientists and technicians, from both academic and business areas, is essential in order to ease the development of systems which can meet the demands of today’s society. Technology transfer in this field is still a challenge and, for that reason, this type of contributions are notably considered in this compilation. This book brings in discussions and publications concerning the development of innovative techniques of IoT complex problems. The technical program focuses both on high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 10 chapters were submitted to this book. The editors particularly encouraged and welcomed contributions on AI and distributed computing in IoT applications.Financed by regional government of Castilla y León and FEDER funds

The role of Artificial Intelligence and Distributed computing in IoT applications

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones[EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results

Smart Buildings

This talk presents an efficient cyberphysical platform for the smart management of smart buildings http://www.deepint.net. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart building is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study at Salamanca - Ecocasa. This platform could enable smart building to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques

Smart territories

The concept of smart cities is relatively new in research. Thanks to the colossal advances in Artificial Intelligence that took place over the last decade we are able to do all that that we once thought impossible; we build cities driven by information and technologies. In this keynote, we are going to look at the success stories of smart city-related projects and analyse the factors that led them to success. The development of interactive, reliable and secure systems, both connectionist and symbolic, is often a time-consuming process in which numerous experts are involved. However, intuitive and automated tools like “Deep Intelligence” developed by DCSc and BISITE, facilitate this process. Furthermore, in this talk we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems, as well as the use of edge platforms or fog computing

A Recommendation-based Proposal for Improving Energy Efficiency in Housing

[EN]75% of buildings in the EU are not designed according to any energy efficiency code and around 45%of the world’s energy is used in the residential sector. This is why one of Europe’s biggest energy challenges is to include consumers at the heart of the energy system. The aim of this work is to develop a solution to a problem of such magnitude: to create a system of personalised recommendations to each consumer that contributes to improving the energy efficiency of their home. The data will be obtained from sensorized homes in Salamanca. Some examples of possible recommendations are reducing the temperature of the thermostat, change the time at which the house is ventilated and raise the blinds at a certain time. The system developed is capable of providing these recommendations correctly an-d efficiently

Managing smart cities with deepint.net

In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities

DeepTech – AI-IoT in smart cities

In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities

DeepTech - AI Models in Engineering Solutions

Artificial Intelligence revived in the last decade. The need for progress, the growing processing capacity and the low cost of the Cloud have facilitated the development of new, powerful algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and Convolutional Networks is transforming the way we work and is opening new horizons. Thanks to them, we can now analyse data and obtain unimaginable solutions to today’s problems. Nevertheless, our success is not entirely based on algorithms, it also comes from our ability to follow our “gut” when choosing the best combination of algorithms for an intelligent artefact. It's about approaching engineering with a lot of knowledge and tact. This involves the use of both connectionist and symbolic systems, and of having a full understanding of the algorithms used. Moreover, to address today’s problems we must work with both historical and real-time data. We must fully comprehend the problem, its time evolution, as well as the relevance and implications of each piece of data, etc. It is also important to consider development time, costs and the ability to create systems that will interact with their environment, will connect with the objects that surround them and will manage the data they obtain in a reliable manner

Efficient Deployment of DeepTech AI Models in Engineering Solutions

The blockchain system, appeared in 2009 together with the virtual currency bitcoin, is a record of digital transactions based on a huge database in which all financial operations carried out with electronic currency are registered. The Blockchain (or chain of blocks) is a shared database that works as a book for the record of purchase-sale operations or any other transaction. It is the technological base of the operation of bitcoin, for example. It consists of a set of notes that are in a shared online database in which operations, quantities, dates and participants are registered by means of codes. By using cryptographic keys and being distributed by many computers (people), it presents security advantages against manipulation and fraud. A modification in one of the copies would be useless, but the change must be made in all the copies because the database is open and public