A framework for the integration of serious games and the Internet of Things (IoT)

Serious Games and the Internet of Things are research topics of high interest. The integration of these two domains has the potential for innovative new applications. This paper presents a framework for the combination of Serious Games and the Internet of Things. In addition, we present the system architecture for a Smart Serious Game ( SSG ) developed for measuring student engagement, and define the difference between an event driven game and an SSG. This paper also includes the updated data algorithms for representing student engagement as game points, based on further consideration on our previous publication

Scenarios for Educational and Game Activities using Internet of Things Data

Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. The goal to address the global climate problem requires informing the population on their roles in mitigation actions and adaptation of sustainable behaviors. Addressing climate change and achieve ambitious energy and climate targets requires a change in citizen behavior and consumption practices. IoT sensing and related scenario and practices, which address school children via discovery, gamification, and educational activities, are examined in this paper. Use of seawater sensors in STEM education, that has not previously been addressed, is included in these educational scenaria

Introducing Neuroberry, a platform for pervasive EEG signaling in the IoT domain

The emergence of inexpensive off-the-shelf wireless EEG devices led researchers to explore novel paradigms in the field of Human Computer Interaction. In fact, the compliance of these devices with the IoT principles towards pervasive EEG signaling in smart home environments enables new models of interaction and a different perspective from traditional affective computing. In this paper, the implementation of wireless EEG (Emotiv EPOC and Mindawave) IoT connectivity of real time raw signals, through IoT hardware devices and through the Raspberry Pi 2, is presented

Security and Privacy Issues of Big Data

This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201

Future Energy Networks and the Role of Interactive Gaming as Simulation

As energy systems integration deepens to support the development of a cleaner and more intelligent energy infrastructure, it will be increasingly important for consumers to better understand their relationship to energy systems and to take more proactive roles in managing energy. Foregrounding the importance of systems comprehension, we argue for the strong potential of interactive games to be helpful in engaging consumers in sustainable energy practices, as they can demonstrate complex system dynamics through simulation-based experiences. Focusing on interrogations of engagement and social change posed by gaming theorists and designers, and using several flagship interactive games as points of reference, we discuss the elements of game space that make it capable of simulating complex systems and large-scale implications of energy decisions richly and effectively. We discuss social, technological, and narrative elements of game play, pairing a theoretical investigation with a practical exploration of how energyrelated games can link with data in the real world, with particular emphasis on the emerging Internet of Things. Our conclusions emphasise the importance of game simulation toward the longer-term goal of cultivating more complex patterns of interaction and cultural analysis around energy use; this is based on the assertion that energy, a social resource, must be managed in ways that are equally social

Collaboration of Smart IoT Devices Exemplified With Smart Cupboards

[EN] The variety of smart things connected to Internet hampers the possibility of having a standalone solution for service-centric provisioning in the Internet of Things (IoT). The different features of smart objects in processing capabilities, memory, and size make it difficult for final users to learn the installation and usage of all these devices in collaboration with other IoT objects, hindering the user experience. In this context, we propose a collaboration mechanism for IoT devices based on the multi-agent systems with mobile agents. This paper illustrates the current approach with smart cupboards for potentially tracking memory losses. The user study revealed that users found working products of this approach usable, easy-to-learn and useful, and they agreed that the current approach could provide a high quality of experience not only in the specific case of service-centric IoT devices for tracking memory losses but also in other domains. The learning capability by means of this approach was showed with significant reductions of reaction times and number of errors over the first and second tests with the current approach. System response timesThis work was supported in part by the Dpto. de Innovacion, Investigacion y Universidad del Gobierno de Aragon through the program FEDER Aragon 2014-2020 Construyendo Europa desde Aragon under Grant T49_17R, in part by the University of Zaragoza and the Foundation Ibercaja through the Research Project Construccion de un framework para agilizar el desarrollo de aplicaciones moviles en el ambito de la salud under Grant JIUZ-2017-TEC-03, in part by the Estancias de movilidad en el extranjero Jose Castillejo para jovenes doctores Program, Spanish Ministry of Education, Culture and Sport, under Grant CAS17/00005, in part by the Universidad de Zaragoza, Fundacion Bancaria Ibercaja and Fundacion CAI, Programa Ibercaja-CAI de Estancias de Investigacion, under Grant IT24/16 and Grant IT1/18, in part by the Research Project Desarrollo Colaborativo de Soluciones AAL, Spanish Ministry of Economy and Competitiveness, under Grant TIN2014-57028-R, in part by the Organismo Autonomo Programas Educativos Europeos under Grant 2013-1-CZ1-GRU06-14277, and in part by the Ministerio de Economia y Competitividad through the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento, under Grant TIN2017-84802-C2-1-P.García-Magariño, I.; González-Landero, F.; Amariglio, R.; Lloret, J. (2019). Collaboration of Smart IoT Devices Exemplified With Smart Cupboards. IEEE Access. 7:9881-9892. https://doi.org/10.1109/ACCESS.2018.2890393S98819892

Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations

Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy to design an efficient energy efficiency system is not straightforward; it requires a priori knowledge of existing fusion strategies, their applications and their properties. To this regard, seeking to provide the energy research community with a better understanding of data fusion strategies in building energy saving systems, their principles, advantages, and potential applications, this paper proposes an extensive survey of existing data fusion mechanisms deployed to reduce excessive consumption and promote sustainability. We investigate their conceptualizations, advantages, challenges and drawbacks, as well as performing a taxonomy of existing data fusion strategies and other contributing factors. Following, a comprehensive comparison of the state-of-the-art data fusion based energy efficiency frameworks is conducted using various parameters, including data fusion level, data fusion techniques, behavioral change influencer, behavioral change incentive, recorded data, platform architecture, IoT technology and application scenario. Moreover, a novel method for electrical appliance identification is proposed based on the fusion of 2D local texture descriptors, where 1D power signals are transformed into 2D space and treated as images. The empirical evaluation, conducted on three real datasets, shows promising performance, in which up to 99.68% accuracy and 99.52% F1 score have been attained. In addition, various open research challenges and future orientations to improve data fusion based energy efficiency ecosystems are explored