Utilización de UAVs en entornos medioambientales

Uno de los mayores avances tecnológicos en la última década ha permitido el acercamiento de UAVs (Vehículos aéreos no tripulados por sus siglas del inglés, Unmanned Aerial Vehicles) a la vida cotidiana de las personas. Uno de los principales factores para conseguirlo fue la aparición de los denominados multi-rotores, con una electrónica relativamente sencilla y una parte mecánica bastante menos costosa y compleja que la ya existente por ejemplo en helicópteros tradicionales. Gracias a la combinación de estos factores y a los potenciales usos profesionales para los que se puede sacar partida, se instauró rápidamente entre la sociedad española. Este rápido crecimiento del interés por su aplicación, llevó a legislar su utilización para evitar los posibles incidentes que un uso inadecuado podría llegar a causar. A lo largo de esta sesión se repasa el estado actual de la legislación en España puesto que existe gran incertidumbre sobre qué se puede y qué no se puede hacer con un UAV, prestando especial interés en las posibilidades que abre su aplicación en entornos mediambientales. Del mismo modo, se detalla una propuesta tecnológica que define un estándar que permite monitorizar el estado en tiempo real de los UAVs conectados, pudiendo monitorizar su comportamiento y definir sistemas de seguridad

Smart Cities Simulation Environment for Intelligent Algorithms Evaluation

This article presents an adaptive platform that can simulate the centralized control of different smart city areas. For example, public lighting and intelligent management, public zones of buildings, energy distribution, etc. It can operate the hardware infrastructure and perform optimization both in energy consumption and economic control from a modular architecture which is fully adaptable to most cities. Machine-to-machine (M2M) permits connecting all the sensors of the city so that they provide the platform with a perfect perspective of the global city status. To carry out this optimization, the platform offers the developers a software that operates on the hardware infrastructure and merges various techniques of artificial intelligence (AI) and statistics, such as artificial neural networks (ANN), multi-agent systems (MAS) or a Service Oriented Approach (SOA), forming an Internet of Services (IoS). Different case studies were tested by using the presented platform, and further development is still underway with additional case studies

Swarm-Based Smart City Platform: A Traffic Application

Smart cities are proposed as a medium-term option for all cities. This article aims to propose an architecture that allows cities to provide solutions to interconnect all their elements. The study case focuses in locating and optimized regulation of traffic in cities. However, thanks to the proposed structure and the applied algorithms, the architecture is scalable in size of the sensor network, in functionality or even in the use of resources. A simulation environment that is able to show the operation of the architecture in the same way that a real city would, is presented

An agent-based Internet of Things platform for distributed real time machine control

[EN] The way in which the Internet of Things and the Web of Things improve everyday objects may seem obvious; elements that make up our daily life are increasingly interconnected and it is becoming more common for us to be surrounded by them. However, the possibilities these technologies offer are not only limited to routinely used objects. By adapting these still emerging technologies, any kind of an object can achieve better performance. They can, for example be applied to research tools, to obtain faster search results and improve the user's experience. The presented work follows these lines; we present a Web-operated machine for the study of the behaviour of certain animals. In addition, the proposed architecture favours the addition of cognitive abilities, due to the inclusion of a Multi-Agent System

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

Intelligent system to control electric power distribution networks

The use of high voltage power lines transport involves some risks that may be avoided with periodic reviews as imposed by law in most countries. The objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. To reduce the number of transmission towers (TT) to be reviewed, a virtual organization (VO) based system of agents is proposed in conjunction with different artificial intelligence methods and algorithms. This system is able to propose a sample of TT from a selected set to be reviewed and to ensure that the whole set will have similar values without needing to review all the TT. As a result, the system provides a software solution to manage all the review processes and all the TT of Spain, allowing the review companies to use the application either when they initiate a new review process for a whole line or area of TT, or when they want to place an entirely new set of TT, in which case the system would recommend the best place and the best type of structure to use

A Case Study for a Smart City Energy Management Resources

A physical smart city model environment is used to presents the demonstration of an energy resources management approach. The demand for smart cities has been created by several factors from the governments, society and industry. Thus, smart grids focus on the intelligent management of energy resources in order to maximize the usage of the energy from renewable sources in order to the final consumers feel the positive effects of less expensive (and pollutant) energy sources, namely in their energy bills. A large amount of work is being developed in the energy resources management domain, but an effective and realistic experimentation are still missing. This paper presents a realistic and physical experimentation of the energy resource management. This is done by using a physical smart city model, which includes several consumers, generation units, and electric vehicles.This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. Bruno Canizes is supported by FCT Funds through the SFRH/BD/110678/2015 PhD scholarship.info:eu-repo/semantics/publishedVersio

Smart City: A GECAD-BISITE Energy Management Case Study

This paper presents the demonstration of an energy resources management approach using a physical smart city model environment. Several factors from the industry, governments and society are creating the demand for smart cities. In this scope, smart grids focus on the intelligent management of energy resources in a way that the use of energy from renewable sources can be maximized, and that the final consumers can feel the positive effects of less expensive (and pollutant) energy sources, namely in their energy bills. A large amount of work is being developed in the energy resources management domain, but an effective and realistic experimentation are still missing. This work thus presents an innovative means to enable a realistic, physical, experimentation of the impacts of novel energy resource management models, without affecting consumers. This is done by using a physical smart city model, which includes several consumers, generation units, and electric vehicles.This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 641794 (Project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the Project UID/EEA/00760/2013. Bruno Canizes is supported by FCT Funds through the SFRH/BD/110678/2015 Ph.D. scholarship.info:eu-repo/semantics/publishedVersio

Swarm-based Smart city platform: A traffic application

Smart cities are proposed as a medium-term option for all cities. This article aims to propose an architecture that allows cities to provide solutions to interconnect all their elements. The study case focuses in locating and optimized regulation of traffic in cities. However, thanks to the proposed structure and the applied algorithms, the architecture is scalable in size of the sensor network, in functionality or even in the use of resources. A simulation environment that is able to show the operation of the architecture in the same way that a real city would, is presented

Relationship recommender system in a business and employment-oriented social network

[EN] In the last ten years, social networks have had a great influence on people’s lifestyles and have changed, above all, the way users communicate and relate. This is why, one of the main lines of research in the field of social networks focuses on finding and analyzing possible connections between users. These developments allow users to expand on their network of contacts without having to search among the total set of users. However, there are many types of social networks which attract users with specific needs, these needs influence on the type of contacts users are looking for. Our article proposes a relationship recommender system for a business and employment-oriented social network. The presented system functions by extracting relevant information from the social network which it then uses to adequately recommend new contacts and job offers to users. The recommender system uses information gathered from job offer descriptions, user profiles and users’ actions. Then, different metrics are applied in order to discover new ties that are likely to convert into relationships