Measuring Interaction in Workplaces

Interactions in the workplace have long been studied by the architectural research community, however, in the past, the majority of those contributions focused on single case studies. Drawing on a much larger empirical sample of 27 offices, this chapter aims at establishing a baseline of understanding how the physical structure of office buildings shapes human behaviours of interaction. This may form a foundation for the Human-Computer Interaction (HCI) community to investigate the impact of embedded computer technology on human behaviours inside buildings. Methods of data collection included an analysis of floor plans with Space Syntax techniques and direct observations of space usage patterns. Exploring this data, different patterns emerged: interactions appeared unevenly distributed in space; interaction rates as well as preferences for locations varied by industry; spatial configuration appeared to create affordances for interaction, since unplanned interactions outside of meeting rooms tended to cluster in more visually connected areas of the office; in addition, seven different micro-behaviours of interaction were identified, each of them driven by affordances in both the built environment and the presence of other people; last but not least, locations for interactions showed clear time-space routines. The chapter closes with interpretations of the results, reflecting on the problem of predictability and how these insights could be useful for evidence-based design, but also the HCI community. It also gives an outlook on future developments regarding the constant logging of human behaviours in offices with emerging technologies

Mobile Sensing Systems

[EN] Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.This work has been partially supported by the "Ministerio de Ciencia e Innovacion", through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental", project TEC2011-27516, and by the Polytechnic University of Valencia, through the PAID-05-12 multidisciplinary projects.Macias Lopez, EM.; Suarez Sarmiento, A.; Lloret, J. (2013). Mobile Sensing Systems. Sensors. 13(12):17292-17321. https://doi.org/10.3390/s131217292S1729217321131

An approach to pervasive monitoring in dynamic learning contexts : data sensing, communication support and awareness provision

It is within the capabilities of current technology to support the emerging learning paradigms. These paradigms suggest that today’s learning activities and environments are pervas ive and require a higher level of dynamism than the traditional learning contexts. Therefore, we have to rethink our approach to learning and use technology not only as a digital information support, but also as an instrument to reinforce knowledge, foster collaboration, promote creativity and provide richer learning experiences. Particularly, this thesis was motivated by the rapidly growing number of smartphone users and the fact that these devices are increasingly becoming more and more resource-rich, in terms of their communication and sensing technologies, display capabilities battery autonomy, etc. Hence, this dissertation benefits from the ubiquity and development of mobile technology, aiming to bridge the gap between the challenges posed by modern learning requirements and the capabilities of current technology. The sensors embedded in smartphones can be used to capture diverse behavioural and social aspects of the users. For example, using microphone and Bluetooth is possible to identify conversation patterns, discover users in proximity and detect face-to-face meetings. This fact opens up exciting possibilities to monitor the behaviour of the user and to provide meaningful feedback. This feedback offers useful information that can help people be aware of and reflect on their behaviour and its effects, and take the necessary actions to improve them. Consequently, we propose a pervasive monitoring system that take advantage of the capabilities of modern smartphones, us ing them to s upport the awarenes s provis ion about as pects of the activities that take place in today’s pervas ive learning environments. This pervasive monitoring system provides (i) an autonomous sensing platform to capture complex information about processes and interactions that take place across multiple learning environments, (ii) an on-demand and s elf-m anaged communication infras tructure, and (ii) a dis play facility to provide “awarenes s inform ation” to the s tudents and/or lecturers. For the proposed system, we followed a research approach that have three main components. First, the description of a generalized framework for pervasive sensing that enables collaborative sensing interactions between smartphones and other types of devices. By allowing complex data capture interactions with diverse remote sensors, devices and data sources, this framework allows to improve the information quality while saving energy in the local device. Second, the evaluation, through a real-world deployment, of the suitability of ad hoc networks to support the diverse communication processes required for pervasive monitoring. This component also includes a method to improve the scalability and reduce the costs of these networks. Third, the design of two awareness mechanisms to allow flexible provision of information in dynamic and heterogeneous learning contexts. These mechanisms rely on the use of smartphones as adaptable devices that can be used directly as awareness displays or as communication bridges to enable interaction with other remote displays available in the environment. Diverse aspects of the proposed system were evaluated through a number of simulations, real-world experiments, user studies and prototype evaluations. The experimental evaluation of the data capture and communication aspects of the system provided empirical evidence of the usefulness and suitability of the proposed approach to support the development of pervasive monitoring solutions. In addition, the proof-of-concept deployments of the proposed awareness mechanisms, performed in both laboratory and real-world learning environments, provided quantitative and qualitative indicators that such mechanisms improve the quality of the awareness information and the user experienceLa tecnología moderna tiene capacidad de dar apoyo a los paradigmas de aprendizaje emergentes. Estos paradigmas sugieren que las actividades de aprendizaje actuales, caracterizadas por la ubicuidad de entornos, son más dinámicas y complejas que los contextos de aprendizaje tradicionales. Por tanto, tenemos que reformular nuestro acercamiento al aprendizaje, consiguiendo que la tecnología sirva no solo como mero soporte de información, sino como medio para reforzar el conocimiento, fomentar la colaboración, estimular la creatividad y proporcionar experiencias de aprendizaje enriquecedoras. Esta tesis doctoral está motivada por el vertiginoso crecimiento de usuarios de smartphones y el hecho de que estos son cada vez más potentes en cuanto a tecnologías de comunicación, sensores, displays, autonomía energética, etc. Por tanto, esta tesis aprovecha la ubicuidad y el desarrollo de esta tecnología, con el objetivo de reducir la brecha entre los desafíos del aprendizaje moderno y las capacidades de la tecnología actual. Los sensores integrados en los smartphones pueden ser utilizados para reconocer diversos aspectos del comportamiento individual y social de los usuarios. Por ejemplo, a través del micrófono y el Bluetooth, es posible determinar patrones de conversación, encontrar usuarios cercanos y detectar reuniones presenciales. Este hecho abre un interesante abanico de posibilidades, pudiendo monitorizar aspectos del comportamiento del usuario y proveer un feedback significativo. Dicho feedback, puede ayudar a los usuarios a reflexionar sobre su comportamiento y los efectos que provoca, con el fin de tomar medidas necesarias para mejorarlo. Proponemos un sistema de monitorización generalizado que aproveche las capacidades de los smartphones para proporcionar información a los usuarios, ayudándolos a percibir y tomar conciencia sobre diversos aspectos de las actividades que se desarrollan en contextos de aprendizaje modernos. Este sistema ofrece: (i) una plataforma de detección autónoma, que captura información compleja sobre los procesos e interacciones de aprendizaje; (ii) una infraestructura de comunicación autogestionable y; (iii) un servicio de visualización que provee “información de percepción” a estudiantes y/o profesores. Para la elaboración de este sistema nos hemos centrado en tres áreas de investigación. Primero, la descripción de una infraestructura de detección generalizada, que facilita interacciones entre smartphones y otros dispositivos. Al permitir interacciones complejas para la captura de datos entre diversos sensores, dispositivos y fuentes de datos remotos, esta infraestructura consigue mejorar la calidad de la información y ahorrar energía en el dispositivo local. Segundo, la evaluación, a través de pruebas reales, de la idoneidad de las redes ad hoc como apoyo de los diversos procesos de comunicación requeridos en la monitorización generalizada. Este área incluye un método que incrementa la escalabilidad y reduce el coste de estas redes. Tercero, el diseño de dos mecanismos de percepción que permiten la provisión flexible de información en contextos de aprendizaje dinámicos y heterogéneos. Estos mecanismos descansan en la versatilidad de los smartphones, que pueden ser utilizados directamente como displays de percepción o como puentes de comunicación que habilitan la interacción con otros displays remotos del entorno. Diferentes aspectos del sistema propuesto han sido evaluados a través de simulaciones, experimentos reales, estudios de usuarios y evaluaciones de prototipos. La evaluación experimental proporcionó evidencia empírica de la idoneidad del sistema para apoyar el desarrollo de soluciones de monitorización generalizadas. Además, las pruebas de concepto realizadas tanto en entornos de aprendizajes reales como en el laboratorio, aportaron indicadores cuantitativos y cualitativos de que estos mecanismos mejoran la calidad de la información de percepción y la experiencia del usuario.Postprint (published version

Digital Behaviour Change Interventions to Break and Form Habits

Digital behaviour change interventions, particularly those using pervasive computing technology, hold great promise in supporting users to change their behaviour. However, most interventions fail to take habitual behaviour into account, limiting their potential impact. This failure is partly driven by a plethora of overlapping behaviour change theories and related strategies that do not consider the role of habits. We critically review the main theories and models used in the research to analyse their application to designing effective habitual behaviour change interventions. We highlight the potential for Dual Process Theory, modern habit theory, and Goal Setting Theory, which together model how users form and break habits, to drive effective digital interventions. We synthesise these theories into an explanatory framework, the Habit Alteration Model, and use it to outline the state of the art. We identify the opportunities and challenges of habit-focused interventions.</jats:p

A privacy-aware and secure system for human memory augmentation

The ubiquity of digital sensors embedded in today's mobile and wearable devices (e.g., smartphones, wearable cameras, wristbands) has made technology more intertwined with our life. Among many other things, this allows us to seamlessly log our daily experiences in increasing numbers and quality, a process known as ``lifelogging''. This practice produces a great amount of pictures and videos that can potentially improve human memory. Consider how a single photograph can bring back distant childhood memories, or how a song can help us reminisce about our last vacation. Such a vision of a ``memory augmentation system'' can offer considerable benefits, but it also raises new security and privacy challenges. Maybe obviously, a system that captures everywhere we go, and everything we say, see, and do, is greatly increasing the danger to our privacy. Any data breach of such a memory repository, whether accidental or malicious, could negatively impact both our professional and private reputation. In addition, the threat of memory manipulation might be the most worrisome aspect of a memory augmentation system: if an attacker is able to remove, add, or change our captured information, the resulting data may implant memories in our heads that never took place, or, in turn, accelerate the loss of other memories. Starting from such key challenges, this thesis investigates how to design secure memory augmentation systems. In the course of this research, we develop tools and prototypes that can be applied by researchers and system engineers to develop pervasive applications that help users capture and later recall episodic memories in a secure fashion. We build trusted sensors and protocols to securely capture and store experience data, and secure software for the secure and privacy-aware exchange of experience data with others. We explore the suitability of various access control models to put users in control of the plethora of data that the system captures on their behalf. We also explore the possibility of using in situ physical gestures to control different aspects regarding the capturing and sharing of experience data. Ultimately, this thesis contributes to the design and development of secure systems for memory augmentation

Targeting the automatic: Nonconscious behaviour change using technology

Digital interventions have great potential to support people to change their behaviour. However, most interventions focus on strategies that target limited conscious resources, reducing their potential impact. We outline how these may fail in the longer-term due to issues with theory, users and technology. We propose an alternative: the direct targeting of nonconscious processes to achieve behaviour change. We synthesise Dual Process Theory, modern habit theory and Goal Setting Theory, which together model how users form and break nonconscious behaviours, into an explanatory framework to explore nonconscious behaviour change interventions. We explore the theoretical and practical implications of this approach, and apply it to a series of empirical studies. The studies explore nonconscious-targeting interventions across a continuum of conscious attention required at the point of behavioural action, from high (just-in-time reminders within Implementation Intentions) to medium (training paradigms within cognitive bias modification) to low (subliminal priming). The findings show that these single-nonconscious-target interventions have mixed results in in-the-wild and semi-controlled conditions. We conclude by outlining how interventions might strategically deploy multiple interventions that target the nonconscious at differing levels of conscious attention, and by identifying promising avenues of future research

Sense and Sensibility in a Pervasive World

The increasing popularity of location based social services such as Facebook Places, Foursquare and Google Latitude, solicits a new trend in fusing social networking with real world sensing. The availability of a wide range of sensing technologies in our everyday environment presents an opportunity to further enrich social networking systems with fine-grained real-world sensing. However, the introduction of passive sensing into a social networking applica- tion disrupts the traditional, user-initiated input to social services, raising both privacy and acceptability concerns. In this work we present an empirical study of the introduction of a sensor-driven social sharing application within the working environment of a research institution. Our study is based on a real deployment of a system that involves location tracking, conversation monitoring, and interaction with physical objects. By utilizing surveys, interviews and experience sampling techniques, we report on our findings regarding privacy and user experience is- sues, and significant factors that can affect acceptability of such services by the users. Our results suggest that such systems deliver significant value in the form of self reflection and comparison with others, while privacy concerns are raised primarily by the limited control over the way individuals are projected to their peers