A machine learning approach for indirect human presence detection using IoT devices

The recent increased democratization of technology led to the appearance of new devices dedicated to the improvement of our daily living and working spaces, capable of being remotely controlled through the internet and interoperability with other systems. In this context, human presence detection is fundamental for several purposes, such has: further automization, usage pattern learning, problem detection (illness, or intruder), etc. Current intrusion detection devices usually have flaws depending on type and many times are not coordinated for better performance. Coordinating the devices for higher level operation however requires a device, or software, that is able communicate and control them. Muzzley is a company that tries to solve this issue by creating a mobile application where the user can register all its devices and control them from there. In this dissertation we propose an approach to human presence detection using metrics based on messages between devices and the Muzzley platform. The idea is that the detection does not rely on information from specific presence detectors, but that it is able to achieve its purpose by analyzing the patterns of interactions with the devices. For this, anonimyzed datasets created by the Muzzley platform are submitted to an extensive processing in order to create meaningful features that will then be used with a machine learning algorithm for training and testing. The main contributions of this study is the processing done to create meaningful information for the task, the demonstration of the capabilities of the interactions between these devices and platforms for human presence detection, and the methods used to improve the performance of the approach.A recente maior democratização da tecnologia contribuiu para o aumento da disponibilidade de dispositivos dedicados à melhoria dos nossos espaços de vivência e trabalho, capazes de controlo remoto pela internet e de interoperabilidade com outros. É neste contexto que a detecção de presença humana é fundamental pois: permite a automatização de acções, a aprendizagem de padrões de uso, a detecção de problemas de doença ou intrusão, etc. Dispositivos específicos de detecção de presença normalmente tem falhas dependendo da sua natureza, e não costumam estar coordenados de forma a melhorar a performance. Coordenar os aparelhos de forma a obter um nível mais inteligente de uso requer um outro dispositivo ou software capaz de comunicar e controlar os outros. A Muzzley é uma empresa que criou uma aplicação móvel onde os utilizadores podem registar todos os seus dispositivos e depois controla-los a partir do programa. Esta dissertação propõe uma abordagem para a detecção de presença baseada na utilização de métricas extraídas das mensagens entre os dispositivos e a plataforma da Muzzley. A ideia é que a detecção não será feita por informação de sensores específicos mas sim pela analise de padrões de interacções com os dispositivos. Conjuntos de dados anónimos criados na plataforma serão submetidos a uma fase extensa de processamento de forma a criar atributos interessantes para o treino e teste de algoritmos de aprendizagem automática. As contribuições principais deste estudo são os algoritmos de processamento construídos para a criação da informação relevante para a tarefa, a demonstração da capacidade do uso destas interações para a detecção de presença, e os métodos usados de forma a melhorar a performance da abordagem

Adaptation to TV delays based on the user behavior towards a cheating-free second screen entertainment

Comunicação apresentada no ICEC, Isip International Conference on Entertainment Computing, 30 setembro a 2 de outubro 2015, Trondheim, NoruegaRecent advances in technology created new opportunities to enhance TV personalization, providing viewers with individualized ways to watch TV and to interact with its content. Second screen applications are promising vehicles to enhance the viewers’ experiences, but researchers need to take into account the effect that the TV delay has on viewers, in particular when watching broadcasted live events. In this paper, we propose a software-based solution to deal with TV delays. It is mainly directed for a gaming context in which the user has the means to control the synchronisation between the second screen application and the TV content. Taking this scenario into account, we implemented a cheating-detection mechanism to cope with the potential exploitation of the system by its users

Personalising the user experience of a mobile health application towards Patient Engagement

Stuttering is a multifactorial speech disorder that usually has several impacts on daily life, especially regarding loss of confidence in social situations and increased anxiety levels. BroiStu is a mobile health application that was developed to address the impacts of stuttering on people who stutter, allowing them to be more aware of their speech disorder in their everyday life. The personalisation of the user experience may be particularly important to maintain the patient engaged with the application towards a long-term use to take full advantage of the application’s features. This paper presents the implementation of personalisation aspects in BroiStu, introducing the model that is being followed, describing the features used, and presenting the results obtained with a preliminary experiment. The personalisation mechanisms are provided by a cloud-based platform that is designed to serve different applications. Interesting findings and further work are presented.info:eu-repo/semantics/publishedVersio

A feasibility study

Funding Information: This work is funded by Fundação para a Ciência e Tecnologia (FCT) through a Ph.D. Studentship grant (SFRH/BD/96899/2013), and supported by NOVA LINCS Research Center, which is partially funded by UID/CEC/04516/2020, granted by FCT. Publisher Copyright: © 2021 Owner/Author.We live surrounded by the most varied computing devices, which may give us the opportunity to combine them to form a unified and richer user experience. Considering this opportunity, we created the UnaxY Framework to support the development of applications with UI components distributed by co-located devices. This paper is focused on a feasibility study based on two prototype applications created using UnaxY. We performed user studies to evaluate concepts associated to this type of applications and the framework they were based on. We had a special interest in assessing how managing the application state and collaborating across devices would be perceived and received by users. The results are positive and clearly indicate that we should continue developing solutions that support a generalized implementation of applications with the user interaction spanning multiple devices.publishersversionpublishe

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved