Rubén Mulero

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[u' @article{sanchez-corcuera_smart_2019, title = {Smart cities survey: {Technologies}, application domains and challenges for the cities of the future}, volume = {15}, issn = {1550-1477}, shorttitle = {Smart cities survey}, url = {https://doi.org/10.1177/1550147719853984}, doi = {10.1177/1550147719853984}, abstract = {The introduction of the Information and Communication Technologies throughout the last decades has created a trend of providing daily objects with smartness, aiming to make human life more comfortable. The paradigm of Smart Cities arises as a response to the goal of creating the city of the future, where (1) the well-being and rights of their citizens are guaranteed, (2) industry and (3) urban planning is assessed from an environmental and sustainable viewpoint. Smart Cities still face some challenges in their implementation, but gradually more research projects of Smart Cities are funded and executed. Moreover, cities from all around the globe are implementing Smart City features to improve services or the quality of life of their citizens. Through this article, (1) we go through various definitions of Smart Cities in the literature, (2) we review the technologies and methodologies used nowadays, (3) we summarise the different domains of applications where these technologies and methodologies are applied (e.g. health and education), (4) we show the cities that have integrated the Smart City paradigm in their daily functioning and (5) we provide a review of the open research challenges. Finally, we discuss about the future opportunities for Smart Cities and the issues that must be tackled in order to move towards the cities of the future.}, language = {en}, number = {6}, urldate = {2019-06-10}, journal = {International Journal of Distributed Sensor Networks}, author = {S\xe1nchez-Corcuera, Ruben and Nu\xf1ez-Marcos, Adri\xe1n and Sesma-Solance, Jesus and Bilbao-Jayo, Aritz and Mulero, Rub\xe9n and Zulaika, Unai and Azkune, Gorka and Almeida, Aitor}, month = jun, year = {2019}, keywords = {Artificial Intelligence, IF1.151, IoT, Q4, Survey, architecture, co-creation, e-government, futuraal, smart cities}, pages = {1550147719853984}, } ']

[u' @article{almeida_critical_2019, title = {A critical analysis of an {IoT}\u2014aware {AAL} system for elderly monitoring}, volume = {97}, issn = {0167-739X}, url = {http://www.sciencedirect.com/science/article/pii/S0167739X18321769}, doi = {10.1016/j.future.2019.03.019}, abstract = {A growing number of elderly people (65+ years old) are affected by particular conditions, such as Mild Cognitive Impairment (MCI) and frailty, which are characterized by a gradual cognitive and physical decline. Early symptoms may spread across years and often they are noticed only at late stages, when the outcomes remain irrevocable and require costly intervention plans. Therefore, the clinical utility of early detecting these conditions is of substantial importance in order to avoid hospitalization and lessen the socio-economic costs of caring, while it may also significantly improve elderly people\u2019s quality of life. This work deals with a critical performance analysis of an Internet of Things aware Ambient Assisted Living (AAL) system for elderly monitoring. The analysis is focused on three main system components: (i) the City-wide data capturing layer, (ii) the Cloud-based centralized data management repository, and (iii) the risk analysis and prediction module. Each module can provide different operating modes, therefore the critical analysis aims at defining which are the best solutions according to context\u2019s needs. The proposed system architecture is used by the H2020 City4Age project to support geriatricians for the early detection of MCI and frailty conditions.}, urldate = {2019-03-22}, journal = {Future Generation Computer Systems}, author = {Almeida, Aitor and Mulero, Rub\xe9n and Rametta, Piercosimo and Uro\u0161evi\u0107, Vladimir and Andri\u0107, Marina and Patrono, Luigi}, month = aug, year = {2019}, keywords = {AAL, AI for health, Ambient Assisted Living, Ambient assisted living, Big data, City4Age, Data analytics, Internet of Things, Internet of things, IoT, Performance, Q1, Smart Environments, elderly people, healthcare, if6.125, pervasive computing, smart cities}, pages = {598--619} }']

[u' @article{mulero_iot-aware_2018, title = {An {IoT}-aware {Approach} for {Elderly}-{Friendly} {Cities}}, volume = {PP}, doi = {10.1109/ACCESS.2018.2800161}, abstract = {The ever-growing life expectancy of people requires the adoption of proper solutions for addressing the particular needs of elderly people in a sustainable way, both from service provision and economic point of view. Mild Cognitive Impairments (MCI) and frailty are typical examples of elderly conditions which, if not timely addressed, can turn out into more complex diseases that are harder and costlier to treat. Information and Communication Technologies (ICTs), and in particular Internet of Things (IoT) technologies, can foster the creation of monitoring and intervention systems, both on an Ambient Assisted Living (AAL) and Smart City scope, for early detecting behavioral changes in elderly people. This allows to timely detect any potential risky situation and properly intervene, with benefits in terms of treatment\u2019s costs. In this context, as part of the H2020-funded City4Age project, this paper presents the data capturing and data management layers of the whole City4Age platform. In particular, this work deals with an unobtrusive data gathering system implementation to collect data about daily activities of elderly people, and with the implementation of the related Linked Open Data (LOD)-based data management system. The collected data are then used by other layers of the platform to perform risk detection algorithms and generate the proper customized interventions. Through the validation of some use-cases, it is demonstrated how this scalable approach, also characterized by unobtrusive and low-cost sensing technologies, can produce data with a high level of abstraction useful to define a risk profile of each elderly person.}, number = {99}, journal = {IEEE Access}, author = {Mulero, Rub\xe9n and Almeida, Aitor and Azkune, Gorka and Abril, Patricia and Arredondo, Maria Teresa and Paramo, Miguel and Patrono, Luigi and Rametta, Piercosimo and Sergi, Ilaria}, year = {2018}, keywords = {AI for health, Artificial Intelligence, City4Age, IoT, Linked Open Data, Middleware, Q1, Senior citizens, Smart City, jcr4.098, machine learning, smart cities, smart environments}, pages = {1--1}, } ']

[u' @inproceedings{almeida_performance_2018, address = {Split, Croatia}, title = {A {Performance} {Analysis} of an {IoT}-aware {Elderly} {Monitoring} {System}}, abstract = {The growing average age of the urban population, with an increasing number of 65+ years old citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly\u2019s environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper is focused on a performance analysis of three main blocks of an IoT-aware monitoring system: (i) data capturing in home and in the city, (ii) data store and management in the Cloud and, (iii) data analytics. Critical points in the system architecture have been highlighted trying also to define potential solutions able to overcome them. The analyzed system architecture is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) and frailty conditions.}, booktitle = {Proceeedings of the 3rd {International} {Conference} on {Smart} and {Sustainable} {Technologies}}, author = {Almeida, Aitor and Mulero, Rub\xe9n and Patrono, Luigi and Rametta, Piercosimo and Urosevic, Vladimir and Andric, Marina}, month = jun, year = {2018}, keywords = {AAL, Ambient Assisted Living, City4Age, IoT, Linked Open Data, Smart City, ambient assisted cities, elderly people, healthcare} }']

[u' @article{mulero_towards_2018, title = {Towards ambient assisted cities using linked data and data analysis}, issn = {1868-5137, 1868-5145}, url = {https://link.springer.com/article/10.1007/s12652-018-0916-y}, doi = {10.1007/s12652-018-0916-y}, abstract = {As citizens\u2019 age increases, smart cities must adapt to help them to age properly. The objective of the City4Age project is to create the future ambient assisted cities that will help the citizens to deal with mild cognitive impairments (MCI) and frailty. In this paper we present two of the tools developed during the project. The first one is a city-wide context-manager, which allows to store the citizens information using a semantic representation and share it following the linked open data paradigm. The second one are the individual care monitoring dashboards, which use the stored information to help the caregivers to analyze and interpret the citizens\u2019 behaviour, allowing to detect risks related to MCI and frailty.}, language = {en}, urldate = {2018-07-02}, journal = {Journal of Ambient Intelligence and Humanized Computing}, author = {Mulero, Rub\xe9n and Urosevic, Vladimir and Almeida, Aitor and Tatsiopoulos, Christos}, month = jun, year = {2018}, keywords = {AAL, AI for health, Ambient Assisted Living, Artificial Intelligence, City4Age, Data analysis, IF1.910, Linked Open Data, Q3, ambient assisted cities, machine learning, smart cities}, pages = {1--19}, } ']

[u' @inproceedings{patrono_innovative_2017, address = {Split}, title = {An {Innovative} {Approach} for {Elderly} {Behavioral} {Analisys} by adopting enabling {IoT} {Technologies}}, abstract = {As the average age of the citizens increases, cities must provide new services for the emerging problem. The City4Age problem aims to provide meaningful interventions to address the problems related to Mild Cognitive Impairment and Frailty in elderly citizens. As part of the City4Age project we have developed a flexible and scalable data capturing and management infrastructure which combines both the Internet of Things and Linked Open Data paradigms. A proof-of-concept validation illustrates how data are collected, managed and computed by the proposed system to make them available for MCI and frailty risk detection algorithms and for third parties.}, booktitle = {Proceedings of the 25th {International} {Conference} on {Software}, {Telecommunications} and {Computer} {Networks}}, author = {Patrono, Luigi and Rametta, Piercosimo and Sergi, Ilaria and Mulero, Rub\xe9n and Almeida, Aitor}, month = sep, year = {2017}, keywords = {AI for health, Ambient Assisted Living, Artificial Intelligence, BLE, City4Age, IoT, Ontology, core-b, embedded systems, machine learning, semantic reasoning, semantic technologies}, } ']

[u' @article{almeida_iot-aware_2017, title = {An {IoT}-aware {Architecture} for {Collecting} and {Managing} data related to {Elderly} {Behavior}}, volume = {2017}, issn = {1530-8669}, url = {https://www.hindawi.com/journals/wcmc/2017/5051915/}, doi = {10.1155/2017/5051915}, abstract = {The world population will be made up of a growing number of elderly people in the near future. Aged people are characterized by some physical and cognitive diseases, like mild cognitive impairment (MCI) and frailty, that, if not timely diagnosed, could turn into more severe diseases, like Alzheimer disease, thus implying high costs for treatments and cares. Information and Communication Technologies (ICTs) enabling the Internet of Things (IoT) can be adopted to create frameworks for monitoring elderly behavior which, alongside normal clinical procedures, can help geriatricians to early detect behavioral changes related to such pathologies and to provide customized interventions. As part of the City4Age project, this work describes a novel approach for collecting and managing data about elderly behavior during their normal activities. The data capturing layer is an unobtrusive and low-cost sensing infrastructure abstracting the heterogeneity of physical devices, while the data management layer easily manages the huge quantity of sensed data, giving them semantic meaning and fostering data shareability. This work provides a functional validation of the proposed architecture and introduces how the data it manages can be used by the whole City4Age platform to early identify risks related to MCI/frailty and promptly intervene.}, language = {English}, number = {5051915}, journal = {Wireless Communications and Mobile Computing}, author = {Almeida, Aitor and Fiore, Alessandro and Mainetti, Luca and Mulero, Rub\xe9n and Patrono, Luigi and Rametta, Piercosimo}, month = dec, year = {2017}, keywords = {City4Age, IoT, Linked Open Data, intelligent environments, jcr0.869, q4, smart cities}, pages = {17} }']

[u' @inproceedings{mulero_linked_2017, address = {San Francisco, USA}, title = {Linked {Open} {Data} {Management} in {Ambient} {Assisted} {Cities}}, abstract = {Linked Open Data in smart cities are an emerging source of open information comprising the needs and requirements of the citizens. However, there are some limitations when it is necessary to store data in sets of different abstraction and aggregation levels. In this paper, we present a new approach to provide smart cities with a tool for storing the data from citizens that provides the ability to select the type of abstraction or aggregation level required in each moment. In addition, the paper presents a novel way to share semantic data following the Linked Open Data paradigm by using a rule engine based reasoner inferring new statements based on spatio-temporal rules.}, booktitle = {Proceedings of the 14th {IEEE} {International} {Conference} on {Ubiquitous} {Intelligence} and {Computing}}, author = {Mulero, Rub\xe9n and Urosevic, Vladimir and Almeida, Aitor}, month = jul, year = {2017}, keywords = {AI for health, Ambient Assisted Living, Artificial Intelligence, City4Age, Fuseki, ISI, Linked Open Data, Rule engine, core-b, machine learning, semantic reasoning, semantic web, smart cities, sparql}, } ']

[u' @inproceedings{mulero_aal_2017, address = {Split}, title = {An {AAL} system based on {IoT} {Technologies} and {Linked} {Open} {Data} for elderly monitoring in {Smart} {Cities}}, abstract = {The average age growing of the urban population, with an increasing number of 65+ citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly\u2019s environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper presents a city-wide general IoT-based sensing infrastructure and a data management layer providing some REST and Linked Open Data Application Programming Interfaces (APIs) that collect and present data related to elderly people. In particular, this architecure is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) disease.}, booktitle = {2nd {International} {Multidisciplinary} {Conference} on {Computer} and {Energy} {Science}}, author = {Mulero, Rub\xe9n and Almeida, Aitor and Azkune, Gorka and Mainetti, Luca and Mighali, Vincenzo and Patrono, Luigi and Rametta, Piercosimo and Sergi, Ilaria}, month = jul, year = {2017}, keywords = {AI for health, Ambient Assisted Living, Artificial Intelligence, City4Age, Internet of Things, IoT, Linked Open Data, intelligent environments, machine learning, semantic inference, smart cities, sparql}, } ']