Ricardo S Alonso

Dr. Ricardo S Alonso

Universidad Internacional De La Rioja, Logroño, La Rioja, Spain
+1
orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2019 in Future Generation Computer Systems
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Journal Article
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ISInés Sittón-Candanedo
Inés Sittón-Candanedo
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso
Juan CorchadoJuan Corchado
Juan Corchado
SRSara Rodríguez-González
Sara Rodríguez-González
Roberto Casado-VaraRoberto Casado-Vara
Roberto Casado-Vara

31 July 2019 in Sensors
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Journal Article
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Inés Sittón-CandanedoInés Sittón-Candanedo
Inés Sittón-Candanedo
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso
Óscar García GarcíaÓscar García García
Óscar García García
Lilia MuñozLilia Muñoz
Lilia Muñoz
Sara Rodríguez GonzálezSara Rodríguez González
Sara Rodríguez González
The Internet of Things (IoT) has become one of the most widely research paradigms, having received much attention from the research community in the last few years. IoT is the paradigm that creates an internet-connected world, where all the everyday objects capture data from our environment and adapt it to our needs. However, the implementation of IoT is a challenging task and all the implementation scenarios require the use of different technologies and the emergence of new ones, such as Edge Computing (EC). EC allows for more secure and efficient data processing in real time, achieving better performance and results. Energy efficiency is one of the most interesting IoT scenarios. In this scenario sensors, actuators and smart devices interact to generate a large volume of data associated with energy consumption. This work proposes the use of an Edge-IoT platform and a Social Computing framework to build a system aimed to smart energy efficiency in a public building scenario. The system has been evaluated in a public building and the results make evident the notable benefits that come from applying Edge Computing to both energy efficiency scenarios and the framework itself. Those benefits included reduced data transfer from the IoT-Edge to the Cloud and reduced Cloud, computing and network resource costs.

1 February 2013 in Information Sciences
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Journal Article
Closed access
DTDante I. Tapia
Dante I. Tapia
JFJuan A. Fraile
Juan A. Fraile
Sara Rodríguez GonzálezSara Rodríguez González
Sara Rodríguez González
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso
Juan CorchadoJuan Corchado
Juan Corchado

27 November 2009 in Journal of Ambient Intelligence and Humanized Computing
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DTDante I. Tapia
Dante I. Tapia
AAAjith Abraham
Ajith Abraham
Juan CorchadoJuan Corchado
Juan Corchado
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso

11 April 2017 in Sensors
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Óscar García GarcíaÓscar García García
Óscar García García
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso
Javier PrietoJavier Prieto
Javier Prieto
Juan CorchadoJuan Corchado
Juan Corchado
The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings.

20 June 2024 in Sensors
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Journal Article
Open access
PDF file
PNPablo Negre
Pablo Negre
Ricardo S AlonsoRicardo S Alonso
Ricardo S Alonso
Alfonso Gonzalez-BrionesAlfonso Gonzalez-Briones
Alfonso Gonzalez-Briones
Javier PrietoJavier Prieto
Javier Prieto
Sara Rodríguez GonzálezSara Rodríguez González
Sara Rodríguez González
Physical aggression is a serious and widespread problem in society, affecting people worldwide. It impacts nearly every aspect of life. While some studies explore the root causes of violent behavior, others focus on urban planning in high-crime areas. Real-time violence detection, powered by artificial intelligence, offers a direct and efficient solution, reducing the need for extensive human supervision and saving lives. This paper is a continuation of a systematic mapping study and its objective is to provide a comprehensive and up-to-date review of AI-based video violence detection, specifically in physical assaults. Regarding violence detection, the following have been grouped and categorized from the review of the selected papers: 21 challenges that remain to be solved, 28 datasets that have been created in recent years, 21 keyframe extraction methods, 16 types of algorithm inputs, as well as a wide variety of algorithm combinations and their corresponding accuracy results. Given the lack of recent reviews dealing with the detection of violence in video, this study is considered necessary and relevant.