Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

Rincon, J. A.; Poza-Lujan, Jose-Luis; Julián, Vicente; Posadas-Yagüe, Juan-Luis; Carrascosa, Carlos

doi:10.1371/journal.pone.0149665

Cited by 14 publications

(6 citation statements)

References 40 publications

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“…Smart resources have been proposed, by the authors of this paper, in previous studies [33]. Smart resources ( Figure 5) allow high connection flexibility, as the features are offered as services.…”

Section: Proposed Architecturementioning

confidence: 99%

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

Poza-Lujan

Posadas-Yagüe

Simó-Ten

et al. 2019

Sensors

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Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. Smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). Smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2–4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices.

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Section: Proposed Architecturementioning

confidence: 99%

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

Poza-Lujan

Posadas-Yagüe

Simó-Ten

et al. 2019

Sensors

Self Cite

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“…On the other hand, in the IVE Workspace, there are those that have a virtual representation, the Inhabitant Agents and the IVE Artifacts. Moreover, this last kind of workspace allows more specific subclasses: Smart Device Artifacts (SDA) [25] and HumanImmersed Agents. The SDA are specialized IVE Artifacts, allowing the developer to make a connection with the real world.…”

Section: Ejacalive (Emotional Jason Cartago Implemented Intelligent Vmentioning

confidence: 99%

“…Unfortunately, due to the fragility of the elderly people and the alpha version of the robot, tests on real environment and with real people were not possible. But that restriction has given way to the enhancement of the EJaCalIVE [25], with the introduction of extended emotion representation, artifacts (and its enhancements like smart devices), and social emotion representation. In fact, these developments are now the part of the core ecosystem operation; that is, the EJaCalIVE will be used even when real users and robot are interacting with each other.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Using Emotions in Intelligent Virtual Environments: The EJaCalIVE Framework

Rincon

Costa

Nováis

et al. 2017

Wireless Communications and Mobile Computing

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Nowadays, there is a need to provide new applications which allow the definition and implementation of safe environments that attends to the user needs and increases their wellbeing. In this sense, this paper introduces the EJaCalIVE framework which allows the creation of emotional virtual environments that incorporate agents, eHealth related devices, human actors, and emotions projecting them virtually and managing the interaction between all the elements. In this way, the proposed framework allows the design and programming of intelligent virtual environments, as well as the simulation and detection of human emotions which can be used for the improvement of the decision-making processes of the developed entities. The paper also shows a case study that enforces the need of this framework in common environments like nursing homes or assisted living facilities. Concretely, the case study proposes the simulation of a residence for the elderly. The main goal is to have an emotion-based simulation to train an assistance robot avoiding the complexity involved in working with the real elders. The main advantage of the proposed framework is to provide a safe environment, that is, an environment where users are able to interact safely with the system.

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“…In this way, it is possible to access a system that allows to distinguish between authorised objects (such To study how different types of devices can cooperate, the Smart Resource model used in previous researches has been used [21]. Smart resources allow high connection flexibility since the features are offered as services.…”

Section: Introductionmentioning

confidence: 99%

Smart Resources for Smart Cities: Distributed Architecture to Integrate Sensor Information

Poza-Lujan¹,

Posadas-Yagüe²,

Simó-Ten³

et al. 2019

Preprint

Self Cite

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Objects recognition is a necessary task in smart city environments. This recognition can be used in processes such as the reconstruction of the environment map or the intelligent navigation of vehicles. This paper proposes an architecture that integrates heterogeneous distributed information to recognize objects in intelligent environments. The architecture is based on the IoT / Industry 4.0 model to interconnect the devices, called Smart Resources. Smart Resources can process local sensor data and send information to other devices. These other devices can be located in the same operating range, the Edge, in the same intranet, the Fog, or on the Internet, the Cloud. Smart Resources must have an intelligent layer in order to be able to process the information. A system with two Smart Resources equipped with different image sensors has been implemented to validate the architecture. Experiments show that the integration of information increases the certainty in the recognition of objects between 2\% and 4\%. Consequently, in the field of intelligent environments, it seems appropriate to provide the devices with intelligence, but also capabilities to collaborate closely with other devices.

show abstract

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

Cited by 14 publications

References 40 publications

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

Using Emotions in Intelligent Virtual Environments: The EJaCalIVE Framework

Smart Resources for Smart Cities: Distributed Architecture to Integrate Sensor Information

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