The Tango Panopticon project merges art with technology to create a live and synchronous art experience which is just as much about the participants as it is about the observers. The goal of this project is to create a dialogue between observers of the event in the hopes of creating new social connections where there were none before. This goal is achieved by allowing observers to view the event from anywhere around the world on a computer via the internet and participate in a dialogue with other users on the website. The other objective of this project is to create a multimedia internet platform for other art projects to use. Other artists that are interested in hosting their own live synchronous event will be able to use the platform we have created and customize it to the specific needs of their project.

Wireless sensor networks (WSNs) have gained attention in recent years with the proliferation of the micro-electro-mechanical systems, which has led to the development of smart sensors. Smart sensors has brought WSNs under the spotlight and has created numerous different areas of research such as; energy consumption, convergence, network structures, deployment methods, time delay, and communication protocols. Convergence rates associated with information propagations of the networks will be questioned in this thesis. Mobility is an expensive process in terms of the associated energy costs. In a sensor network, mobility has significant overhead in terms of closing old connections and creating new connections as mobile sensor nodes move from one location to another. Despite these drawbacks, mobility helps a sensor network reach an agreement more quickly. Adding few mobile nodes to an otherwise static network will significantly improve the network’s ability to reach consensus. This paper shows the effect of the mobility on convergence rate of the wireless sensor networks, through Eigenvalue analysis, modeling and simulation.

abstract: The mobile crowdsensing (MCS) applications leverage the user data to derive useful information by data-driven evaluation of innovative user contexts and gathering of information at a high data rate. Such access to context-rich data can potentially enable computationally intensive crowd-sourcing applications such as tracking a missing person or capturing a highlight video of an event. Using snippets and pictures captured from multiple mobile phone cameras with specific contexts can improve the data acquired in such applications. These MCS applications require efficient processing and analysis to generate results in real time. A human user, mobile device and their interactions cause a change in context on the mobile device affecting the quality contextual data that is gathered. Usage of MCS data in real-time mobile applications is challenging due to the complex inter-relationship between: a) availability of context, context is available with the mobile phones and not with the cloud, b) cost of data transfer to remote cloud servers, both in terms of communication time and energy, and c) availability of local computational resources on the mobile phone, computation may lead to rapid battery drain or increased response time. The resource-constrained mobile devices need to offload some of their computation. This thesis proposes ContextAiDe an end-end architecture for data-driven distributed applications aware of human mobile interactions using Edge computing. Edge processing supports real-time applications by reducing communication costs. The goal is to optimize the quality and the cost of acquiring the data using a) modeling and prediction of mobile user contexts, b) efficient strategies of scheduling application tasks on heterogeneous devices including multi-core devices such as GPU c) power-aware scheduling of virtual machine (VM) applications in cloud infrastructure e.g. elastic VMs. ContextAiDe middleware is integrated into the mobile application via Android API. The evaluation consists of overheads and costs analysis in the scenario of ``perpetrator tracking" application on the cloud, fog servers, and mobile devices. LifeMap data sets containing actual sensor data traces from mobile devices are used to simulate the application run for large scale evaluation. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2019

This paper aims at giving answers to the question of how and why mobile device usage patterns differ in China, Germany and the United States of America. Triangulation was chosen as the appropriate research method: qualitative date from focus groups is complemented with quantitative date from an online questionnaire. Firstly, a short overview over past research results on psychological differences between people from different cultures is given. Then, qualitative data gathered in focus groups is presented. Quantitative data on mobile device usage patterns from an online questionnaire in the three countries is presented. About 300 questionnaires were completed and evaluated. Many statistically significant effects from the quasi-variable culture could be found. For example, although almost all participants from all three cultures use mobile devices for communication purposes, the usage frequencies of other functions differ strongly. Cultures differ also in the acceptance of autonomous interventions by a technical system. Probable explanations for these differences and their consequences on HMI design are discussed. / Diese Veröffentlichung soll die Frage beantworten, wie und warum sich die Nutzungsmuster von mobilen Endgeräten in China, Deutschland und den USA unterscheiden. Als angemessene Untersuchungsmethode wurde die Triangulation ausgewählt: Qualitative Daten aus Fokusgruppen werden ergänzt durch quantitative Daten aus einem Online-Fragebogen. Zuerst wird ein kurzer Überblick über bestehende Forschungsergebnisse über psychologische Unterschiede zwischen Menschen aus verschiedenen Kulturen gegeben. Anschließend werden qualitative Daten aus Fokusgruppen und quantitative Daten aus einem Online-Fragebogen über Nutzungsmuster von mobilen Endgeräten präsentiert. Mehr als 300 Fragebögen wurden ausgefüllt und ausgewertet. Viele statistisch signifikante Auswirkungen der Quasi-Variable Kultur konnten gefunden werden. Während beispielsweise fast alle Teilnehmer aus allen drei Kulturen mobile Endgeräte für Kommunikationszwecke nutzen, unterscheiden sich die Nutzungshäufigkeiten anderer Funktionen stark. Die Kulturen unterscheiden sich auch in der Akzeptanz von autonomen Eingriffen durch ein technisches System. Mögliche Erklärungen für diese Unterschiede und deren Folgen für die Gestaltung von Mensch-Maschine-Schnittstellen werden diskutiert.

Bei der Entwicklung von mobilen Informationssystemen stehen die Entwickler oft vor immer wiederkehrenden Entwurfsentscheidungen, die von einer Anzahl noch unstrukturierter Kriterien abhängen. Den kompletten Entscheidungsprozess für jedes einzelne Projekt von vorne bis hinten zu durchlaufen ist ineffizient und fehleranfällig, trotzdem gibt es noch keine umfassende Sammlung von „Best Practices“, die diesen Prozess verkürzen könnte. Wir präsentieren daher die Grundlagen eines Klassifikationsschemas für mobile Informationssysteme, das Entwicklern hilft, Anwendungen anhand von Anforderungen auf höherer Ebene zu klassifizieren und entsprechende Architekturentscheidungen zu treffen. Im Anschluss an die Diskussion der vorgestellten Kriterien schlagen wir Erweiterungen des Klassifikationsschemas und Folgerungen, die daraus gezogen werden können, vor.

<div> <div> <div> <p>Billions of “smart” things in our lives have been equipped with various sensors. Current devices, such as smartphones, smartwatches, tablets, and VR/AR headsets, are equipped with a variety of embedded sensors, e.g. accelerometer, gyroscope, magnetometer, camera, GPS sensor, etc. Based on these sensor data, many technologies have been developed to track human motion at different granularities and to enable new applications. This dissertation examines two challenging problems in human motion tracking. One problem is the ID association issue when utilizing external sensors to simultaneously track multiple people. Although an “outside” system can track all human movements in a designated area, it needs to digitally associate each tracking trajectory to the corresponding person, or say the smart device carried by that person, to provide customized service based on the tracking results. Another problem is the inaccuracy caused by limited sensing information when merely using the embedded sensors located on the devices being tracked. Since sensor data may contain inevitable noises and there is no external beacon used as a reference point for calibration, it is hard to accurately track human motion only with internal sensors.</p><p>In this dissertation, we focus on applying multimodal sensing to perform human motion tracking in mobile systems. To address the two above problems separately, we conduct the following research works. (1) The first work seeks to enable public cameras to send personalized messages to people without knowing their phone addresses. We build a system which utilizes the users’ motion patterns captured by the cameras as their communication addresses, and depends on their smartphones to locally compare the sensor data with the addresses and to accept the correct messages. To protect user privacy, the system requires no data from the users and transforms the motion patterns into low-dimensional codes to prevent motion leaks. (2) To enhance distinguishability and scalability of the camera-to-human communication system, we introduce context features which include both motion patterns and ambience features (e.g. magnetic field, Wi-Fi fingerprint, etc.) to identify people. The enhanced system achieves higher association accuracy and is demonstrated to work with dense people in a retailer, with a fixed-length packet overhead. The first two works explore the potential of widely deployed surveillance cameras and provide a generic underlay to various practical applications, such as automatic audio guide, indoor localization, and sending safety alerts. (3) We close this dissertation with a fine-grained motion tracking system which aims to track the positions of two hand-held motion controllers in a mobile VR system. To achieve high tracking accuracy without external sensors, we introduce new types of information, e.g. ultrasonic ranging among the headset and the controllers, and a kinematic arm model. Effectively fusing this additional information with inertial sensing generates accurate controller positions in real time. Compared with commodity mobile VR controllers which only support rotational tracking, our system provides an interactive VR experience by letting the user actually move the controllers’ positions in a VR scene. To summarize, this dissertation shows that multimodal sensing can further explore the potential power in sensor data and can take sensor-based applications to the next generation of innovation.</p><div><br></div></div></div></div><div><div><div> </div> </div> </div>

In this thesis, a framework for Quality of Service provisioning in next generation wireless access networks is proposed. The framework aims at providing a differentiated service treatment to real-time (delay-sensitive) and non-real-time (delay-tolerant) multimedia traffic flows at the link layer. Novel techniques such as bandwidth compaction, channel reservation, and channel degradation are proposed. Using these techniques, we develop a call admission control algorithm and a call control block as part of the QoS framework. The performance of the framework is captured through analytical modeling and simulation experiments. By analytical modeling, the average carried traffic and the worst case buffer requirements for real-time and non-real-time calls are estimated. Simulation results show a 21% improvement in call admission probability of real-time calls, and a 17% improvement for non-real-time calls, when bandwidth compaction is employed. The channel reservation technique shows a 12% improvement in call admission probability in comparison with another proposed scheme in the literature.

Mobile computing allows individuals to bring computing with them into the outdoors. This creates a new situation in which individuals can stay connected even when trying to "get away from it all." Questions arise from this juxtaposition regarding whether the inclusion of computing in these activities is a positive or a negative. Evidence exists supporting both conclusions. We posit that computing can contribute positively to outdoor recreation without distracting. This dissertation details work undertaken in two phases which explores how computing can accomplish this goal. Phase 1 explored how individuals are already using computing technology in hiking, and culminated with the development of a model describing individuals' decisions regarding technology use on the trail. In Phase 2, we developed a vision which navigates the tension between the connection technology provides to our day-to-day lives and the desire to disconnect, along with prototypes which serve as an embodiment of this vision. We found that computing is in wide use by hikers, and through qualitative data analysis we developed a Two Worlds model which describes their decisions regarding technology use when hiking. This model provides a space which can be probed and explored in future work. Our vision guides careful growth in the inclusion of computing in outdoor recreation, allowing computing to support activities without becoming a distraction. Our work makes important empirical, theoretical, and artifact contributions to the field of HCI. It also identifies interesting areas of exploration, some of which have already informed the development of our Two Worlds model, and some of which remain largely unexplored. In this sense, our work has both blazed new trails in exploring computing's place in outdoor recreation and identified "side trails" for further exploration by ourselves and others. We look forward to this work and its results.

Mobile technologies have the potential to improve patient monitoring, medical decision making and in general the efficiency and quality of health delivery. They also pose new security and privacy challenges. The objectives of this work are to (i) Explore and define security and privacy requirements on the example of a post-surgical care application, and (ii) Develop and test a pilot implementation Post-Surgical Care Studies of surgical out- comes indicate that timely treatment of the most common complications in compliance with established post-surgical regiments greatly improve success rates. The goal of our pilot application is to enable physician to optimally synthesize and apply patient directed best medical practices to prevent post-operative complications in an individualized patient/procedure specific fashion. We propose a framework for a secure protocol to enable doctors to check most common complications for their patient during in-hospital post- surgical care. We also implemented our construction and cryptographic protocols as an iPhone application on the iOS using existing cryptographic services and libraries.

After nearly 2 decades of advances in information and communications technologies (ICT) including social media, mobile, analytics, and cloud computing, disaster response agencies in the United States have not been able to improve alignment between ICT-based information and disaster response actions. This grounded theory study explored emergency response ICT managers' understanding of how social media, mobile, analytics, and cloud computing technologies (SMAC) are related to and can inform disaster response strategies. Sociotechnical theory served as the conceptual framework to ground the study. Data were collected from document reviews and semistructured interviews with 9 ICT managers from emergency management agencies in the state of Hawaii who had experience in responding to major disasters. The data were analyzed using open, axial coding, and selective coding. Three elements of a theory emerged from the findings: (a) the ICT managers were hesitant about SMAC technologies replacing first responder's radios to interoperate between emergency response agencies during major disasters, (b) the ICT managers were receptive to converging conventional ICT with SMAC technologies, and (c) the ICT managers were receptive to joining legacy information sharing strategies with new information sharing strategies based on SMAC technologies. The emergent theory offers a framework for aligning SMAC technologies and disaster response strategies. The implications for positive social change include reduced interoperability failures between disaster agencies during major catastrophes, which may lower the risk of casualties and deaths to emergency responders and disaster victims, thus benefiting them and their communities.