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

Taxi services and the carsharing alternative: a case study of Valencia city

[EN] The public's awareness of pollution in cities is growing. The decrease of carbon dioxide emissions from the use of fossil-fuel-powered cars stands out among the different viable alternatives. To this purpose, more sustainable options, such as carsharing fleets, could be used to replace private automobiles and other services such as taxis. This type of vehicle, which is usually electric, is becoming more common in cities, providing a green mobility option. In this research, we use multi-agent simulations to examine the efficiency of the current taxi fleet in Valencia. After that, we evaluate various carsharing fleet arrangements. Our findings demonstrate the possibility for a mix of the two types of fleets to meet present demand while also improving the city's sustainability.This work is partially supported by grant RTI2018-095390-B-C31 funded by MCIN/AEI/ 10.13039/501100011033 and by "ERDF A way of making Europe". Pasqual Martí is supported by grant ACIF/2021/259 funded by the "Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana". Jaume Jordán is supported by grant IJC2020-045683-I funded by MCIN/AEI/ 10.13039/501100011033 and by "European Union NextGenerationEU/PRTR". Pablo Chamoso is supported by grant CCTT3/20/SA/0002 (AIR-SCity project), funded by Institute for Business Competitiveness of Castilla y León, and the European Regional Development Fund.Martí, P.; Jordán, J.; Chamoso, P.; Julian, V. (2022). Taxi services and the carsharing alternative: a case study of valencia city. Mathematical Biosciences and Engineering. 19(7):6680-6698. https://doi.org/10.3934/mbe.202231466806698197L. Rayle, D. Dai, N. Chan, R. Cervero, S. Shaheen, Just a better taxi? a survey-based comparison of taxis, transit, and ridesourcing services in san francisco, Transp. Policy, 45 (2016), 168–178. https://doi.org/10.1016/j.tranpol.2015.10.004R. Katzev, Car sharing: a new approach to urban transportation problems, Anal. Soc. Issues Public Policy, 3 (2003), 65–86. https://doi.org/10.1111/j.1530-2415.2003.00015.xM. Namazu, H. Dowlatabadi, Vehicle ownership reduction: a comparison of one-way and two-way carsharing systems, Transp. Policy, 64 (2018), 38–50. https://doi.org/10.1016/j.tranpol.2017.11.001A. Kolleck, Does car-sharing reduce car ownership? empirical evidence from Germany, Sustainability, 13 (2021), 7384. https://doi.org/10.3390/su13137384J. Firnkorn, M. Müller, What will be the environmental effects of new free-floating car-sharing systems? the case of car2go in Ulm, Ecol. Econ., 70 (2011), 1519–1528. https://doi.org/10.1016/j.ecolecon.2011.03.014X. Dong, Y. Cai, J. Cheng, B. Hu, H. Sun, Understanding the competitive advantages of car sharing from the travel-cost perspective, Int. J. Environ. Res. Public Health, 17 (2020), 4666. https://doi.org/10.3390/ijerph17134666T. Yoon, C. R. Cherry, M. S. Ryerson, J. E. Bell, Carsharing demand estimation and fleet simulation with EV adoption, J. Cleaner Prod., 206 (2019), 1051–1058. https://doi.org/10.1016/j.jclepro.2018.09.124J. Palanca, A. Terrasa, C. Carrascosa, V. Julián, Simfleet: a new transport fleet simulator based on MAS, in International Conference on Practical Applications of Agents and Multi-Agent Systems, (2019), 257–264. https://doi.org/10.1007/978-3-030-24299-2_22P. Martí, J. Jordán, V. Julián, Carsharing in valencia: analysing an alternative to taxi fleets, in Practical Applications of Agents and Multi-Agent Systems, Springer, (2021), 270–282. https://doi.org/10.1007/978-3-030-85710-3_23M. E. Gregori, J. P. Cámara, G. A. Bada, A jabber-based multi-agent system platform, in Proceedings of the Fifth International Joint Conference on Autonomous Aagents and Multiagent Systems, (2006), 1282–1284. https://doi.org/10.1145/1160633.1160866P. Martí, J. Jordán, J. Palanca, V. Julian, Free-floating carsharing in SimFleet, in International Conference on Intelligent Data Engineering and Automated Learning, Springer, (2020), 221–232. https://doi.org/10.1007/978-3-030-62362-3_20P. Martí, J. Jordán, J. Palanca, V. Julian, Load generators for automatic simulation of urban fleets, in International Conference on Practical Applications of Agents and Multi-Agent Systems, Springer, (2020), 394–405. https://doi.org/10.1007/978-3-030-51999-5_33N. Firdausiyah, E. Taniguchi, A. G. Qureshi, Modeling city logistics using adaptive dynamic programming based multi-agent simulation, Transp. Res. Part E: Logist. Transp. Rev., 125 (2019), 74–96. https://doi.org/10.1016/j.tre.2019.02.011C. Standing, F. Jie, T. Le, S. Standing, S. Biermann, Analysis of the use and perception of shared mobility: a case study in western Australia, Sustainability, 13 (2021), 8766. https://doi.org/10.3390/su13168766H. Qin, E. Su, Y. Wang, J. Li, Branch-and-price-and-cut for the electric vehicle relocation problem in one-way carsharing systems, Omega, 109 (2022), 102609. https://doi.org/10.1016/j.omega.2022.102609H. Habekotté, Optimizing Carsharing Policies for a New Generation-A Quest on How to Upscale Carsharing as Part of Sustainable Mobility Systems in Dutch Urban Regions, PhD thesis, University of Groningen, 2021.A. Ciociola, D. Markudova, L. Vassio, D. Giordano, M. Mellia, M. Meo, Impact of charging infrastructure and policies on electric car sharing systems, in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), IEEE, (2020), 1–6. https://doi.org/10.1109/ITSC45102.2020.9294282J. Schlüter, A. Bossert, P. Rössy, M. Kersting, Impact assessment of autonomous demand responsive transport as a link between urban and rural areas, Res. Trans. Bus. Manage., 39 (2021), 100613. https://doi.org/10.1016/j.rtbm.2020.100613F. Javanshour, H. Dia, G. Duncan, R. Abduljabbar, S. Liyanage, Performance evaluation of station-based autonomous on-demand car-sharing systems, IEEE Trans. Intell. Transp. Syst., 2021 (2021), 1–12. https://doi.org/10.1109/TITS.2021.3071869P. Martí, J. Jordán, J. Palanca, V. Julian, Charging stations and mobility data generators for agent-based simulations, Neurocomputing, 484 (2022), 196–210. https://doi.org/10.1016/j.neucom.2021.06.098D. I. Grozev, D. E. Topchu, D. I. Miteva, Assessment of CO2 emissions released from the taxi vehicle fleet in Ruse, in Proceedings of the 2nd Virtual Multidisciplinary Conference, (2014), 484–487.J. Jordán, P. Martí, J. Palanca, V. Julian, V. Botti, Interurban electric vehicle charging stations through genetic algorithms, in International Conference on Hybrid Artificial Intelligence Systems, Springer, (2021), 101–112. https://doi.org/10.1007/978-3-030-86271-8_9J. Jordán, J. Palanca, E. del Val, V. Julian, V. Botti, Localization of charging stations for electric vehicles using genetic algorithms, Neurocomputing, 452 (2021), 416–423. https://doi.org/10.1016/j.neucom.2019.11.12

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

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

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

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 Cyber Victimization Discovery on Twitter

[EN] The advancement of technologies, the promotion of smart-phones, and social networking have led to a high tendency among users to spend more time online interacting with each other via the available technologies. This is because they help overcome physical limitations and save time and energy by doing everything online. The rapid growth in this tendency has created the need for extra protection, by creating new rules and policies. However, sometimes users interrupt these rules and policies through unethical behavior. For example, bullying on social media platforms is a type of cyber victimization that can cause serious harm to individuals, leading to suicide. A firm step towards protecting the cyber society from victimization is to detect the topics that trigger the feeling of being a victim. In this paper, the focus is on Twitter, but it can be expanded to other platforms. The proposed method discovers cyber victimization by detecting the type of behavior leading to them being a victim. It consists of a text classification model, that is trained with a collected dataset of the official news since 2000, about suicide, self-harm, and cyberbullying. Results show that LinearSVC performs slightly better with an accuracy of 96%.This research has been supported by the project "Intelligent and sustainable mobility supported by multi-agent systems and edge computing (InEDGE-Mobility): Towards Sustainable Intelligent Mobility: Blockchain-based framework for IoT Security", Reference: RTI2018-095390-B-C31/32/33, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), the State Research Agency (AEI) and the European Regional Development Fund (FEDER).Shoeibi, N.; Shoeibi, N.; Julian, V.; Ossowski, S.; González Arrieta, A.; Chamoso, P. (2021). Smart Cyber Victimization Discovery on Twitter. Springer. 289-299. https://doi.org/10.1007/978-3-030-78901-5_2528929

A machine learning approach to evaluating the relationship between dental extraction and craniofacial growth in adolescents

There may be multiple reasons for tooth extraction, such as deep cavities, an infection that has destroyed an important portion of the tooth or the bone that surrounds it, or for orthodontic reasons, such as the lack of space for all the teeth in the mouth. In the case of orthodontics, however, there is a relationship between tooth extraction and the craniofacial morphological pattern. The purpose of this study is to establish whether such a relationship exists in adolescents and to evaluate it and to serve as a tool to support medical decision making. Machine Learning techniques can now be applied to datasets to discover relationships between different variables. Thus, this study involves the application of a series of Machine Learning techniques to a dataset containing information on orthodontic tooth extraction in adolescents. It has been discovered that by following simple rules it is possible to identify the need of treatment in 98.7% of the cases, while the remaining can be regarded as “limited cases”, in which an expert’s opinion is necessary.- (UIDB/00319/2020