Privacy-respecting Reward Generation and Accumulation for Participatory Sensing Applications

Participatory or crowd-sensing applications process sensory data contributed by users and transform them to simple visualizations (such as for example noise or pollution levels) that help create an accurate representation of the surrounding environment. Although contributed data is of great interest to individuals, the involvement of citizens and community groups, however, is still limited. Hence, incentivizing users to increase participation seems crucial for the success of participatory sensing. In this paper, we develop a privacy-preserving rewarding scheme which allows campaign administrators to reward users for the data they contribute. Our system of anonymous tokens allow users to enjoy the benefits of participation while at the same time ensuring their anonymity. Moreover, rewards can be accumulated together thus further increasing the level of privacy offered by the system. Our proposal is coupled with a security analysis showing the privacy-preserving character of the system along with an efficiency analysis demonstrating the feasibility of our approach in realistic deployment settings

Incentivizing Participation in Crowd-Sensing Applications Through Fair and Private Bitcoin Rewards

In this work we develop a rewarding framework that can be used to enhance existing crowd-sensing applications. Although a core requirement of such systems is user engagement, people may be reluctant to participate because sensitive information about them may be leaked or inferred from submitted data. The use of monetary rewards can help incentivize participation, thereby increasing not only the amount but also the quality of sensed data. Our framework allows users to submit data and obtain Bitcoin payments in a privacy-preserving manner, preventing curious providers from linking the data or the payments back to the user. At the same time, it prevents malicious user behavior such as double-redeeming attempts, where a user tries to obtain rewards for multiple submissions of the same data. More importantly, it ensures the fairness of the exchange in a completely trustless manner; by relying on the Blockchain, the trust placed on third parties in traditional fair exchange protocols is eliminated. Finally, our system is highly efficient as most of the protocol steps do not utilize the Blockchain network. When they do, only the simplest of Blockchain transactions are used as opposed to prior works that are based on the use of more complex smart contracts.publishedVersionPeer reviewe

Ecosystemic Evolution Feeded by Smart Systems

Information Society is advancing along a route of ecosystemic evolution. ICT and Internet advancements, together with the progression of the systemic approach for enhancement and application of Smart Systems, are grounding such an evolution. The needed approach is therefore expected to evolve by increasingly fitting into the basic requirements of a significant general enhancement of human and social well-being, within all spheres of life (public, private, professional). This implies enhancing and exploiting the net-living virtual space, to make it a virtuous beneficial integration of the real-life space. Meanwhile, contextual evolution of smart cities is aiming at strongly empowering that ecosystemic approach by enhancing and diffusing net-living benefits over our own lived territory, while also incisively targeting a new stable socio-economic local development, according to social, ecological, and economic sustainability requirements. This territorial focus matches with a new glocal vision, which enables a more effective diffusion of benefits in terms of well-being, thus moderating the current global vision primarily fed by a global-scale market development view. Basic technological advancements have thus to be pursued at the system-level. They include system architecting for virtualization of functions, data integration and sharing, flexible basic service composition, and end-service personalization viability, for the operation and interoperation of smart systems, supporting effective net-living advancements in all application fields. Increasing and basically mandatory importance must also be increasingly reserved for human–technical and social–technical factors, as well as to the associated need of empowering the cross-disciplinary approach for related research and innovation. The prospected eco-systemic impact also implies a social pro-active participation, as well as coping with possible negative effects of net-living in terms of social exclusion and isolation, which require incisive actions for a conformal socio-cultural development. In this concern, speed, continuity, and expected long-term duration of innovation processes, pushed by basic technological advancements, make ecosystemic requirements stricter. This evolution requires also a new approach, targeting development of the needed basic and vocational education for net-living, which is to be considered as an engine for the development of the related ‘new living know-how’, as well as of the conformal ‘new making know-how’

Roadmap for the uptake of the Citizen Observatories' knowledge base

WeObserve brought together several Citizen Observatory projects to share and consolidate knowledge and identify best practices. Many of the insights gained have been synthesised into this detailed research and innovation roadmap for future Citizen Observatories, outlining focus areas, dedicated pathways and proposed actions in each of them. The aim of this roadmap is to outline a dynamic landscape and provide actionable pathways to further advance Citizen Observatories’ capabilities and impacts in the future. It is targeted at Citizen Observatory practitioners (research institutions, civil society organisations, public authorities and others) for conceptualising and directing key aspects of future Citizen Observatories; at national funding agencies of EU member states to identify potential scenarios for funding Citizen Observatories nationally; as well as for the European Commission as a consultation document for shaping Horizon Europe programme funding calls

The Contribution of Indigenous Ecological Knowledge in Conservation of Enguserosambu Community Forest, Tanzania

Community managed forests constitute a significant proportion of the world\u27s forests, however, little is known regarding their condition or the details of how they are managed. Documented benefits of community managed forest include poverty alleviation and in some places a decrease in the rate of deforestation. Although some community based forests do not satisfy the IUCN definition of a protected areas, they provide valuable long term sustainability of forest products and many are also rich in biodiversity and support landscape conservation strategies. Forests are also home to many cultures including the indigenous people. Indigenous communities surrounding forest areas and other protected areas have developed patterns of resource use and management that reflect their intimate knowledge of local environments and ecosystems. However, indigenous knowledge is rarely documented or incorporated into science based or government run conservation planning. It is therefore the aim of this research to examine the contribution of indigenous ecological knowledge in the conservation of Enguserosambu Community Forest and surrounding rangelands. Specifically, the research aimed to; understand social mechanisms supporting indigenous ecological knowledge generation, accumulation and transmission, to examine the role of local indigenous institutions in supporting conservation of Enguserosambu Community Forest, and to assess if time-series aerial imagery support historical forest management practices shared as oral histories about land-use change by the communities. Case study design was used to explore the phenomenon in detail. Purposeful sampling was used to recruit research participants that could provide information rich in detail about indigenous forest management practices in the study area. Four villages were surveyed. Individual and group semi-structured interviews were conducted with customary elders, village leaders, forest user groups, NGO\u27s, and forest officers. One focus group discussion was conducted with a community conservation trust. A total of 57 individuals were interviewed, of which 19 were females. Interviews session lasted between 30 minutes and 2 hours. Most of the interviews were audio recorded. Interviews were conducted in either Swahili or Maa language. In case of the latter, translator was used during the interview process. Field noted were also recorded each time the researcher visited the villages. Thematic analysis was carried out for qualitative information using NVivo 10. To compare oral history with land cover change, satellite images with 30m spatial resolution were acquired from Landsat 7 and 8 for land cover change analysis. Satellite Imagery from February 2000 and February 2015 were selected for analysis. ArcGIS 10.2 was used to analyze satellite images for forest cover change

Measuring and designing social mechanisms using mobile phones

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-168).A key challenge of data-driven social science is the gathering of high quality multi-dimensional datasets. A second challenge relates to the design and execution of social experiments in the real world that are as reliable as those within a controlled laboratory, yet yield more practical results. We introduce the Social Functional Mechanism-design and Relationship Imaging, or "SocialfMRI" - an approach that enhances existing computational social science methodologies by bridging rich data collection strategies with experimental interventions. In this thesis, we demonstrate the value of the Social fMRI approach in our Friends and Family study. We transformed a young-family residential community into a living laboratory for 15 months, through a very fine-grained and longitudinal data collection process combined with targeted experimental interventions. Through the derived dataset of unprecedented quality, the Social fMRI approach allows us to gain insights into intricate social mechanisms and interpersonal relationships within the community in ways not previously possible. This thesis delivers the following contributions: (1) A methodology combining a rich-data experimental approach together with carefully designed interventions, (2) a system supporting the methodology - implemented, field-tested, and released to the world as an open-source framework with a growing community of users, (3) a dataset collected using the system, comprising what is, to date, the richest real-world dataset of its genre, (4) a very large set of experimental findings that contribute to our understanding of important research questions in computational social science in addition to demonstrating the methodology's potential. Among the results described in this thesis are the design and evaluation of a novel mechanism for social support in a health-related context, the observation that the diffusion of mobile applications relies more on the face-to-face interaction ties than on self-perceived friendship ties, and a gained understanding of the evolution of modeling and prediction processes over time and varying sample sizes.by Nadav Aharony.Ph.D

Supporting Diabetes Self-Management with Ubiquitous Computing Technologies: A User-Centered Inquiry

Ubiquitous computing technologies offer opportunities to improve treatments for chronic health conditions. Type 1 diabetes is a compelling use-case for such approaches, given its severity, and need for individuals to make frequent care decisions, informed by complex data. However, current apps, typically based on effortful reflection on collected data, generally show poor adoption, lack vital cognitive and emotional support, and are poorly tailored to users’ actual diabetes decision making processes. This thesis investigates how diabetes apps can be improved from a user-centered perspective. An initial questionnaire-based study investigated how well existing diabetes apps meet user needs. Perceived benefits, limitations, and reasons for low adoption rates were identified. A talk-aloud study of detailed user interactions with diabetes logging apps was conducted to characterize the benefits and limitations of diverse UI elements for T1 diabetes management, and to more precisely identify wider problems with current interaction designs. This led to positing a refined version of Mamykina et al.’s model for diabetes self-management, to account for observed practices, whereby the previously accepted habitual and sensemaking cognitive states are augmented by a posited ‘fluid contextual reasoning’ (FCR) mode, which allows multiple contextual factors to be balanced for dynamic course correction when navigating complex situations, using previously learned knowledge. To investigate user perceptions of the levels and kinds of monitoring anticipated in next generation diabetes decision support systems, a 4-week technology probe, in which participants used multiple networked devices and external data aggregation, was used to frame requirements for user-centered development of such future systems. Integrating all of the above work, an iterative design process was undertaken to create DUETS, a card-based system to facilitate reflection by designers, users, and other stakeholders on diabetes support management systems. The resulting tool and method were then implemented and evaluated through structured sessions with stakeholder focus groups

Geographic Citizen Science Design

Little did Isaac Newton, Charles Darwin and other ‘gentlemen scientists’ know, when they were making their scientific discoveries, that some centuries later they would inspire a new field of scientific practice and innovation, called citizen science. The current growth and availability of citizen science projects and relevant applications to support citizen involvement is massive; every citizen has an opportunity to become a scientist and contribute to a scientific discipline, without having any professional qualifications. With geographic interfaces being the common approach to support collection, analysis and dissemination of data contributed by participants, ‘geographic citizen science’ is being approached from different angles. Geographic Citizen Science Design takes an anthropological and Human-Computer Interaction (HCI) stance to provide the theoretical and methodological foundations to support the design, development and evaluation of citizen science projects and their user-friendly applications. Through a careful selection of case studies in the urban and non-urban contexts of the Global North and South, the chapters provide insights into the design and interaction barriers, as well as on the lessons learned from the engagement of a diverse set of participants; for example, literate and non-literate people with a range of technical skills, and with different cultural backgrounds. Looking at the field through the lenses of specific case studies, the book captures the current state of the art in research and development of geographic citizen science and provides critical insight to inform technological innovation and future research in this area