In recent years, Wi-Fi technologies have become very popular and the trend is continuing to climb. Unfortunately, there is a risk to use Wi-Fi networks in range because there is no way to select trustworthy Wi-Fi networks. In this thesis, we focus on ways that can help users to choose the best Wi-Fi network for their needs. In order to help the user to choose the best network, our solution allows the users to rate the networks that they have used. It also checks that their assessments reflect the true network quality that they have experienced by measuring and certifying the quality of service such as delay, jitter and packet loss. The measuring process follows an innovative protocol that certifies the measurement in all cases but one. We mitigate this remaining case thanks to trust and reputation management.
This thesis proposes a new type of information, called hovering information, which is stored in geographical regions and does not rely on any infrastructure but on the mobile devices that populate the respective geographical region, its anchor area. A storage and two retrieval algorithms are proposed. They take advantage of the broadcasting nature of mobile ad hoc networks while controlling the network overhead thanks to a novel mechanism. Further, this thesis studies the persistence, accessibility, critical mass of density of nodes, the messages complexity as well as the resilience to failure of the algorithms. It also proposes a middleware and its respective implementation as an Android service which enables mobile applications to store and retrieve information from geographical regions.
A key concern in the Internet of Things (IoT) has been the integration of mundane objects in the Internet. Although increasingly interconnected, the IoT ecosystem is largely industry-centered. This leads to the creation of limited and incompatible services disempowering users by hampering their participation. In this thesis, we address this issue by empowering users to create, personalize, and distribute services in the IoT ecosystem. We define a general framework for user empowerment relying on the concepts of People, Places, Things and Applications and study their interactions. These concepts are used as design elements to implement an IoT Service Platform. The general framework, the reference implementation and the evaluation provide the design guidelines for building IoT service platforms enabling user empowerment in the IoT.
Scientists, when they read, chain document together. They reuse those chains for understanding a problem, for advancing in their research, or for writing. Systems such as Google Scholar, PubMed, Web of Knowledge, use references contained into scientific documents to link those documents together, but they are using only direct citation. More explicitly, document "a" will refer to document "b" and document "b" might refer to document "c” and those systems will create a link between these documents. But in this case “a” has a connection with “c”, but it is not explicit, therefore those systems cannot create the link. Moreover, the links between documents are not classified by type, they are generic. Users cannot know whether “a” disagree or agree with “b” without reading the document.
Emerging healthcare applications rely on personal mobile devices to monitor patient vital signs and to send it to the hospitals-backend servers for further analysis. However, these devices have limited resources that must be used optimally in order to meet the requirements of healthcare applications end-users: healthcare professionals and their patients. This paper reports on a case study of a cardiac telemonitoring application delivered by the so-called MobiHealth system. This system relies on a commercial device with multiple (wireless) network interfaces (NI). Our study focuses on how the choice of a NI affects the end-to-end applicationpsilas data delay (extremely important in case of patientpsilas emergency) and the energy consumption of the device (relating to the service sustainability while a patient is mobile). Our results show the trade-off between the delay and battery savings achieved by various NI activation strategies in combination with application-data flow adaptation. For a given mobile device, our study shows a gain of 40-90% in battery savings, traded against the higher delays (therefore applicable mainly in non-emergency cases). The insights of our studies can be used for application-data flow adaptation aiming at battery saving and prolonging devicepsilas operation for mobile patients.
Mobile service providers (MoSPs) emerge, propelled by ubiquitous availability of mobile devices and wireless communication infrastructures. MoSPs' customers satisfaction and consequently their revenues, largely depend on the quality of service (QoS) offered by wireless network providers (WNPs) at a particular location and time of a mobile service usage. This chapter presents a novel business method for the MoSP's QoS-assurance process. The method incorporates a location- and time-based QoS-predictions service facilitating the improvement of the WNP's selection process. We introduce and analyse business viability of QoSIS.net, an enterprise that provides the QoS-predictions service to MoSPs or directly to its customers (i.e. in B2B or B2C settings). QoSIS.net provides highly accurate QoS-predictions based on collaborative-sharing of QoS-information by its users. We argue that this business method can improve the MoSP's QoS-assurance process and consequently may increase its revenues, while creating revenues for QoSIS.net.
The experimental setting of Human Mobile Computer Interaction (HCI) studies is moving from the controlled laboratory to the user's daily-life environments, while employing the users' own smartphones. These studies are challenging for both new and expert researchers in human subject studies in the HCI field. Within the last three years, we conducted three different smartphone- based user studies. From these studies, we have derived key challenges that we successfully overcame during their execution. In this paper, we present the outcomes and explain the adopted solutions for the challenges identified in the design, development and execution, and data analysis phases during the user studies. Our goal is to give newcomers and junior researchers a practical view on our conducted studies, and help practitioners to reflect on their own studies and possibly apply the proposed solutions.
Increasingly, we use mobile applications and services in our daily life activities, to support our needs for information, communication or leisure. However, user acceptance of a mobile application depends on at least two conditions; the application's perceived experience and the appropriateness of the application to the user's context and needs. Yet, we have a weak understanding of a mobile user's Quality of Experience (QoE) and the factors influencing it. This paper presents 4 week long, 29 Android phone users study, where we collected both QoE and underlying network's Quality of Service (QoS) measures through a combination of user, application and network data on the user's phones. We aimed to derive and improve the understanding of users' QoE for a set of widely used mobile applications in users' natural environments and different daily context. We present data acquired in the study and discuss implications for mobile applications design.
Inevitably, mobile applications and services on a growing scale assist us in our daily life situations, fulfilling our needs for leisure, entertainment, communication or information. However, user acceptance of a mobile application depends on the application's perceived quality of experience (QoE) and it also includes the criticality of the application to the user's context and situation at hand. Statistics for usage of mobile applications provided via ‘app stores' show that more than 50% of these applications never reach a minimal required user acceptance level, and get removed from the store. However, despite the importance of understanding of the mobile user QoE, a sound methodology for evaluation of this experience, and of factors influencing it, does not exist. Moreover, this QoE relates to the level of quality of service (QoS) provided by the underlying service and network infrastructures, which usually is provided at ‘best-effort' level. Therefore, in our research we aim to provide a set of rigorous and robust methodological steps to be taken to quantify a mobile user QoE in his natural environments and different contexts, and to analyze its relation with the underlying QoS. We aim to evaluate the applicability if the methodology in a large scale mobile user study for a set of widely used mobile applications.
Background: Mental health has long been a neglected problem in global healthcare. The social and economic impacts of conditions affecting the mind are still underestimated. However, in recent years it is becoming more apparent that mental disorders are a growing global concern and there is a necessity of developing novel services and researching effective means of providing interventions to sufferers. Such novel services could include technology-based solutions already used in other healthcare applications but are yet to make their way into standard psychiatric practice. Methods: This manuscript proposes a system where sensors are utilised to devise an “early warning” system for patients with bipolar disorder. The system, containing wearable and environmental sensors, would collect behavioural data independent from the patient's self-report. To test the feasibility of the concept, a prototype system was devised, which was followed by trials including four healthy volunteers as well as a bipolar patient. Results: The sensors utilised in the study yielded behavioural data which may be of significant use in detecting early effects of a bipolar episode. Basic processing performed on particular data inputs provided information about activity patterns in areas, which are usually strongly influenced by the course of Bipolar Disorder. Conclusions: The manuscript discusses the basic usage issues and other barriers which are to be tackled before technology-based approaches to mental care can be successfully rolled out and their true value appraised.
