Designing a Framework to Handle Context Information

In the recent years, a number of context-aware frameworks have been proposed to facilitate the development of context-aware applications. From the experience gained, in this paper we explore the design principles that contextaware platforms should conform to, the functionalities they have to provide and the technologies and tools that can be used for their implementation. Subsequently, we propose a context-aware framework and describe the architecture it adopts, making our own technological selection from the options previously identified

An attitude-based reasoning strategy to enhance interaction with augmented objects

This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his real-time location and orientation and, finally, his active touch and focus interactions with the virtual overlay. The proposed reasoning method has been partially validated through a prototype that handles 2D and 3D visualization interfaces. This framework makes possible to develop in practice the IoT paradigm, augmenting the objects without physically modifying them

Deploying context-aware services: A case study of rapid prototyping

In this contribution, a real experience of rapid design and deployment of context-aware services for an exhibition hall is detailed. The prototype has been built on a combination of a commercial system (which has been customized and improved to satisfy the prototype needs) with an in-home developed context acquisition framework. In order to partially overcome device fragmentation issues, we have focused on the development of web-based context-aware applications. The whole system has been deployed from scratch under real constraints of time and environment. The objective has been to test the integration problems of context-aware systems, in order to infer some conclusions on what it is needed to generalize them

A Development Methodology to Facilitate the Integration of Smart Spaces into the Web of Things

How to create or integrate large Smart Spaces (considered as mash-ups of sensors and actuators) into the paradigm of ?Web of Things? has been the motivation of many recent works. A cutting-edge approach deals with developing and deploying web-enabled embedded devices with two major objectives: 1) to integrate sensor and actuator technologies into everyday objects, and 2) to allow a diversity of devices to plug to Internet. Currently, developers who want to use this Internet-oriented approach need have solid understanding about sensorial platforms and semantic technologies. In this paper we propose a Resource-Oriented and Ontology-Driven Development (ROOD) methodology, based on Model Driven Architecture (MDA), to facilitate to any developer the development and deployment of Smart Spaces. Early evaluations of the ROOD methodology have been successfully accomplished through a partial deployment of a Smart Hotel

Towards a fuzzy-based multi-classifier selection module for activity recognition applications

Performing activity recognition using the information provided by the different sensors embedded in a smartphone face limitations due to the capabilities of those devices when the computations are carried out in the terminal. In this work a fuzzy inference module is implemented in order to decide which classifier is the most appropriate to be used at a specific moment regarding the application requirements and the device context characterized by its battery level, available memory and CPU load. The set of classifiers that is considered is composed of Decision Tables and Trees that have been trained using different number of sensors and features. In addition, some classifiers perform activity recognition regardless of the on-body device position and others rely on the previous recognition of that position to use a classifier that is trained with measurements gathered with the mobile placed on that specific position. The modules implemented show that an evaluation of the classifiers allows sorting them so the fuzzy inference module can choose periodically the one that best suits the device context and application requirements

An RFID-enabled framework to support Ambient Home Care Services

The growing number of elderly in modern societies is encouraging advances in remote assistive solutions to enable sustainable and safe ‘ageing in place’. Among the many technologies which may serve to support Ambient Home Care Systems, RFID is offering a set of differential features which make it suitable to build new interaction schemes while supporting horizontal system’s features such as localization. This paper details the design of a passive RFID-based AHCS, composed by an infrastructure of mobile and static tags and readers controlled by a SOA (service oriented architecture) middleware. The technology possibilities, its drawbacks and integration problems in this application domain are described from a practical approach

Moving forward on u-healthcare: A framework for patient-centric

Delivering remote healthcare services without deteriorating the ‘patient experience’ requires building highly usable and adaptive applications. Efficient context data collection and management make possible to infer extra knowledge on the user’s situation, making easier the design of these advanced ubiquitous applications. This contribution, part of a work in progress which aims at building an operative AmI middleware, presents a generic architecture to provide u-healthcare services, to be delivered both in mobile and home environments. In particular, we address the design of the Context Management Component (CMC), the module that takes context data from the sensing layer and performs data fusion and reasoning to build an aggregated ‘context image’. We especially explain the requirements on data modelling and the functional features that are imposed to the CMC. The resulting logical multilayered architecture -composed by acquisition and fusion, inference and reasoning levels- is detailed, and the technologies needed to develop the Context Management Component are finally specifie

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data