Information technology for active ageing: A review of theory and practice

Active Ageing aims to foster a physically, mentally and socially active lifestyle as a person ages. It is a complex, multi-faceted problem that involves a variety of different actors, such as policy makers, doctors, care givers, family members, friends and, of course, older adults. This review aims to understand the role of a new actor, which increasingly plays the role of enabler and facilitator, i.e., that of the technology provider. The review specifically focuses on Information Technology (IT), with a particular emphasis on software applications, and on how IT can prevent decline, compensate for lost capabilities, aid care, and enhance existing capabilities. The analysis confirms the crucial role of IT in Active Ageing, shows that Active Ageing requires a multidisciplinary approach, and identifies the need for better integration of hardware, software, the environment and the involved actors

A survey on wireless indoor localization from the device perspective

With the marvelous development of wireless techniques and ubiquitous deployment of wireless systems indoors, myriad indoor location-based services (ILBSs) have permeated into numerous aspects of modern life. The most fundamental functionality is to pinpoint the location of the target via wireless devices. According to how wireless devices interact with the target, wireless indoor localization schemes roughly fall into two categories: device based and device free. In device-based localization, a wireless device (e.g., a smartphone) is attached to the target and computes its location through cooperation with other deployed wireless devices. In device-free localization, the target carries no wireless devices, while the wireless infrastructure deployed in the environment determines the target’s location by analyzing its impact on wireless signals. This article is intended to offer a comprehensive state-of-the-art survey on wireless indoor localization from the device perspective. In this survey, we review the recent advances in both modes by elaborating on the underlying wireless modalities, basic localization principles, and data fusion techniques, with special emphasis on emerging trends in (1) leveraging smartphones to integrate wireless and sensor capabilities and extend to the social context for device-based localization, and (2) extracting specific wireless features to trigger novel human-centric device-free localization. We comprehensively compare each scheme in terms of accuracy, cost, scalability, and energy efficiency. Furthermore, we take a first look at intrinsic technical challenges in both categories and identify several open research issues associated with these new challenges.</jats:p

QUEST Hierarchy for Hyperspectral Face Recognition

Face recognition is an attractive biometric due to the ease in which photographs of the human face can be acquired and processed. The non-intrusive ability of many surveillance systems permits face recognition applications to be used in a myriad of environments. Despite decades of impressive research in this area, face recognition still struggles with variations in illumination, pose and expression not to mention the larger challenge of willful circumvention. The integration of supporting contextual information in a fusion hierarchy known as QUalia Exploitation of Sensor Technology (QUEST) is a novel approach for hyperspectral face recognition that results in performance advantages and a robustness not seen in leading face recognition methodologies. This research demonstrates a method for the exploitation of hyperspectral imagery and the intelligent processing of contextual layers of spatial, spectral, and temporal information. This approach illustrates the benefit of integrating spatial and spectral domains of imagery for the automatic extraction and integration of novel soft features (biometric). The establishment of the QUEST methodology for face recognition results in an engineering advantage in both performance and efficiency compared to leading and classical face recognition techniques. An interactive environment for the testing and expansion of this recognition framework is also provided

Ragionamento Temporale Fuzzy per applicazioni Elder Care

Con la fine del secolo scorso nuovi progetti sono stati presi in esame da alcuni gruppi di ricerca con lo scopo di esplorare il concetto di assistenza anziani (spesso etichettato con il termine "elder care"). Fra le molteplici sfumature che questo campo propone, gli sforzi della ricerca universitaria si sono principalmente concentrati nello studio e nella costruzione di sistemi automatici che sfruttino i più recenti sviluppi tecnologici al fine di monitorare il benessere degli anziani e di rispondere ai problemi in cui un utente può incorrere, come cadere o dimenticarsi di assumere i medicinali che gli sono stati prescritti. È in quest'ambito che si sviluppa la presente tesi; gli obiettivi sono due: da un lato ottenere una panoramica delle soluzioni presenti in letteratura e dall'altro proporre una possibile applicazione del sistema di ragionamento temporale fuzzy, sviluppato presso il Dipartimento di Ingegneria dell'Informazione di Padova, allo scopo di monitorare la giornata di un soggetto anziano e suggerire eventuali modifiche per renderla il più possibile conforme al comportamento indicato dal medico curanteope

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

Fine Art Pattern Extraction and Recognition

This is a reprint of articles from the Special Issue published online in the open access journal Journal of Imaging (ISSN 2313-433X) (available at: https://www.mdpi.com/journal/jimaging/special issues/faper2020)

Gaze-Based Human-Robot Interaction by the Brunswick Model

We present a new paradigm for human-robot interaction based on social signal processing, and in particular on the Brunswick model. Originally, the Brunswick model copes with face-to-face dyadic interaction, assuming that the interactants are communicating through a continuous exchange of non verbal social signals, in addition to the spoken messages. Social signals have to be interpreted, thanks to a proper recognition phase that considers visual and audio information. The Brunswick model allows to quantitatively evaluate the quality of the interaction using statistical tools which measure how effective is the recognition phase. In this paper we cast this theory when one of the interactants is a robot; in this case, the recognition phase performed by the robot and the human have to be revised w.r.t. the original model. The model is applied to Berrick, a recent open-source low-cost robotic head platform, where the gazing is the social signal to be considered