Óscar García

Ambient intelligence and collaborative e-learning: a new definition model

The constant evolution of mobile devices and Information Technologies allows users to enjoy a new variety of features that were unimaginable some years ago. In this sense, Ambient Intelligence (AmI) has emerged as a new discipline focused on people and aimed at facilitating their daily activities. This paper proposes a new definition model that helps designers to characterize collaborative e-learning systems based on AmI and Computer Supported Collaborative Learning. The use of mobile devices and Mobile Adhoc Networks is a key aspect in this model as they allow users to access resources from anywhere on demand. The proposed model is applied to a concrete case of study as an example of its application on real scenarios.

ARTIZT: Applying Ambient Intelligence to a Museum Guide Scenario

Museum guides present a great opportunity where the Ambient Intelligence (AmI) paradigm can be successfully applied. Together with pervasive computing, context and location awareness are the AmI features that allow users to receive customized information in a transparent way. In this sense, Real-Time Locating Systems (RTLS) can improve context-awareness in AmI-based systems. This paper presents ARTIZT, an innovative AmI-based museum guide system where a novel RTLS based on the ZigBee protocol provides highly precise users’ position information. Thus, it can be customized the content offered to the users without their explicit interaction, as well as the granularity level provided by the system.

ALZ-MAS 2.0; A Distributed Approach for Alzheimer Health Care

This paper presents ALZ-MAS 2.0; an Ambient Intelligence based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients living in geriatric residences. The system makes use of FUSION@, a multi-agent architecture which facilitates the integration of distributed services and applications to optimize the construction of Ambient Intelligence environments. The architecture optimizes the development of distributed multi-agent systems, where applications and services can communicate in a distributed way, even from mobile devices, independent of a specific programming language or operating system. The results obtained demonstrate that ALZ-MAS 2.0 is far more robust and has better performance than the previous version.

Energy Efficiency in Public Buildings through Context-Aware Social Computing

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.

Cloud-IO: Cloud Computing Platform for the Fast Deployment of Services over Wireless Sensor Networks

In the recent years, a new computing model, known as Cloud Computing, has emerged to react to the explosive growth of the number of devices connected to Internet. Cloud Computing is centered on the user and offers an efficient, secure and elastically scalable way of providing and acquiring services. Likewise, Ambient Intelligence (AmI) is also an emerging paradigm based on ubiquitous computing that proposes new ways of interaction between humans and machines, making technology adapt to the users’ necessities. One of the most important aspects in AmI is the use of context-aware technologies such as Wireless Sensor Networks (WSN) to perceive stimuli from both the users and the environment. In this regard, this paper presents Cloud-IO, a Cloud Computing platform for the fast integration and deployment of services over WSNs.

The n-Core Polaris Real-Time Locating System at the EvAAL Competition

One of the most important technologies used to provide context-awareness in Ambient Assisted Living environments is Wireless Sensor Networks (WSNs). Wireless Sensor Networks comprise an ideal technology to develop Real-Time Locating Systems (RTLS) aimed at indoor environments, where existing global navigation satellite systems do not work correctly. In this sense, Nebusens and the BISITE Research Group of the University of Salamanca have developed n-Core Polaris, a new indoor and outdoor RTLS based on ZigBee WSNs and an innovative set of locating and automation engines. n-Core Polaris is based on the n-Core platform, a hardware and software platform intended for developing and deploying easily and quickly a wide variety of WSN applications based on the ZigBee standard. This paper describes the n-Core Polaris system, as well as the experiments made during the first EvAAL Competition on Indoor Localization and Tracking, whose results demonstrate the effectiveness of n-Core Polaris in indoor environments.

Intelligent Agents and Wireless Sensor Networks: A Healthcare Telemonitoring System

E-healthcare has acquired great importance in recent years and requires the development of innovative solutions. This paper presents a telemonitoring system aimed at enhancing remote healthcare for dependent people at their homes. The system deploys a Service-Oriented Architecture based platform over a heterogeneous Wireless Sensor Networks infrastructure. Furthermore, the information obtained by telemonitoring systems must be managed by intelligent and self-adaptable technologies to provide an adequate interaction between the users and their environment. In the proposed system, the WSNs platform is integrated with a multi-agent architecture so that information gathered by WSN nodes is managed by intelligent agents with reasoning mechanisms.

Wireless Sensor Networks for data acquisition and information fusion: A case study

Data acquisition is one of the most relevant aspects in tele-monitoring systems. Information fusion helps these systems to better unify data collected from different sources. This paper presents a case study that consists of a tele-monitoring system aimed at enhancing remote healthcare for dependent people at their homes. The system deploys a service-oriented architecture over a heterogeneous Wireless Sensor Networks infrastructure to create smart environments. Such architecture can be executed over multiple wireless devices independently of their microcontroller or the programming language they use. Furthermore, the system allows the interconnection of several networks from different wireless technologies, such as ZigBee or Bluetooth. This approach provides the system better flexibility to change its functionalities and components after deployment than other analyzed proposals. The system description, its architecture, and preliminary results of the system prototype implemented in a real environment are presented.

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated.

Evaluating the n-Core Polaris Real-Time Locating System in an Indoor Environment

Context-aware technologies allow Ambient Assisted Living developments to automatically obtain information from users and their environment in a distributed and ubiquitous way. One of the most important technologies used to provide context-awareness is Wireless Sensor Networks (WSN). Wireless Sensor Networks comprise an ideal technology to develop Real-Time Locating Systems (RTLS) aimed at indoor environments, where existing global navigation satellite systems do not work correctly. In this regard, n-Core Polaris is an indoor and outdoor RTLS based on ZigBee WSNs and an innovative set of locating and automation engines. This paper presents the main components of the n-Core Polaris, as well as some experiments made in a real scenario whose results demonstrate the effectiveness of the system in indoor environments.