A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

Indoor localization and navigation using wireless sensor networks is still a big challenge if expensive sensor nodes are not involved. Previous research has shown that in a sparse distributed sensor network the error distance is way too high. Even room accuracy can not be guaranteed. In this paper, an easy-to-use generic positioning framework is proposed, which allows users to plug in a single or multiple positioning algorithms. We illustrate the usability of the framework by discussing a new hybrid positioning solution. The combination of a weighted (range-based) and proximity (range-free) algorithm is made. Roth solutions separately have an average error distance of 13.5m and 2.5m respectively. The latter result is quite accurate due to the fact that our testbeds are not sparse distributed. Our hybrid algorithm has an average error distance of 2.66m only using a selected set of nodes, simulating a sparse distributed sensor network. All our experiments have been executed in the iMinds testbed: namely at "de Zuiderpoort". These algorithms are also deployed in two real-life environments: "De Vooruit" and "De Vijvers"

An IoT-aware AAL System to Capture Behavioral Changes of Elderly People

The ageing of population is a phenomenon that is affecting the majority of developed countries around the world and will soon affect developing economies too. In recent years, both industry and academia are focused on the development of several solutions aimed to guarantee a healthy and safe lifestyle to the elderly. In this context, the behavioral analysis of elderly people can help to prevent the occurrence of Mild Cognitive Impairment (MCI) and frailty problems. The innovative technologies enabling the Internet of Things (IoT) can be used in order to capture personal data for automatically recognizing changes in elderly people behavior in an unobtrusive, low-cost and low-power modality. This work aims to describe the ongoing activities within the City4Age project, funded by the Horizon 2020 Programme of the European Commission, mainly focused on the use of IoT technologies to develop an innovative AAL system able to capture personal data of elderly people in their home and city environments. The proposed architecture has been validated through a proof-of-concept focused mainly on localization issues, collection of ambient parameters, and user-environment interaction aspects

Authoring and Living Next-Generation Location-Based Experiences

Authoring location-based experiences involving multiple participants, collaborating or competing in both indoor and outdoor mixed realities, is extremely complex and bound to serious technical challenges. In this work, we present the first results of the MAGELLAN European project and how these greatly simplify this creative process using novel authoring, augmented reality (AR) and indoor geolocalisation techniques

Ubiquitous Internet in an integrated satellite-terrestrial environment: The SUITED solution

yesThe current Internet architecture appears to not be particularly suited to addressing the emerging needs of new classes of users who wish to gain access to multimedia services made available by ISPs, regardless of their location, while in motion and with a guaranteed level of quality. One of the main objectives of so-called nextgeneration systems is to overcome the limitations of today¿s available Internet by adopting an approach based on the integration of different mobile and fixed networks. The SUITED project moves in this direction since it aims at contributing to the design and deployment of the global mobile broadband system (GMBS), a unique satellite/terrestrial infrastructure ensuring nomadic users access to Internet services with a negotiated QoS. A description of the main features of the GMBS architecture, characterized by the integration of a multisegment access network with a federated ISP network is given in this article. The GMBS multimode terminal is schematically described, and an overview of the so-called QoS-aware mobility management scheme, devised for such a heterogeneous scenario,is provided

Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones

Wireless location technologies and applications

[No abstract available