167 research outputs found

    Qos‐aware approximate query processing for smart cities spatial data streams

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    Large amounts of georeferenced data streams arrive daily to stream processing systems. This is attributable to the overabundance of affordable IoT devices. In addition, interested practitioners desire to exploit Internet of Things (IoT) data streams for strategic decision‐making purposes. However, mobility data are highly skewed and their arrival rates fluctuate. This nature poses an extra challenge on data stream processing systems, which are required in order to achieve prespecified latency and accuracy goals. In this paper, we propose ApproxSSPS, which is a system for approximate processing of geo‐referenced mobility data, at scale with quality of service guarantees. We focus on stateful aggregations (e.g., means, counts) and top‐N queries. ApproxSSPS features a controller that interactively learns the latency statistics and calculates proper sampling rates to meet latency or/and accuracy targets. An overarching trait of ApproxSSPS is its ability to strike a plausible balance between latency and accuracy targets. We evaluate ApproxSSPS on Apache Spark Structured Streaming with real mobility data. We also compared ApproxSSPS against a state‐of‐the‐art online adaptive processing system. Our extensive experiments prove that ApproxSSPS can fulfill latency and accuracy targets with varying sets of parameter configurations and load intensities (i.e., transient peaks in data loads versus slow arriving streams). Moreover, our results show that ApproxSSPS outperforms the baseline counterpart by significant magnitudes. In short, ApproxSSPS is a novel spatial data stream processing system that can deliver real accurate results in a timely manner, by dynamically specifying the limits on data samples

    The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study

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    Background: This paper examines the development of the Connected Health research landscape with a view on providing a historical perspective on existing Connected Health research. Connected Health has become a rapidly growing research field as our healthcare system is facing pressured to become more proactive and patient centred. Objective: We aimed to identify the extent and coverage of the current body of knowledge in Connected Health. With this, we want to identify which topics have drawn the attention of Connected health researchers, and if there are gaps or interdisciplinary opportunities for further research. Methods: We used a systematic mapping study that combines scientific contributions from research on medicine, business, computer science and engineering. We analyse the papers with seven classification criteria, publication source, publication year, research types, empirical types, contribution types research topic and the condition studied in the paper. Results: Altogether, our search resulted in 208 papers which were analysed by a multidisciplinary group of researchers. Our results indicate a slow start for Connected Health research but a more recent steady upswing since 2013. The majority of papers proposed healthcare solutions (37%) or evaluated Connected Health approaches (23%). Case studies (28%) and experiments (26%) were the most popular forms of scientific validation employed. Diabetes, cancer, multiple sclerosis, and heart conditions are among the most prevalent conditions studied. Conclusions: We conclude that Connected Health research seems to be an established field of research, which has been growing strongly during the last five years. There seems to be more focus on technology driven research with a strong contribution from medicine, but business aspects of Connected health are not as much studied

    Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis

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    Reis-Marques, C., Figueiredo, R., & Neto, M. D. C. (2021). Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis. European Journal of Investigation in Health, Psychology and Education, 11(4), 1406-1421. https://doi.org/10.3390/ejihpe11040101 ---------------------------------------------- This work is financed by national funds through FCT—Fundação para a Ciência e a Tecnologia, I. P., under the project “UIDB/04630/2020”.Research related to blockchain is rapidly gaining importance in the higher education. This opportunity collaborates with a proposal for a review of papers on the main blockchain topic. The bibliometric analysis included 61 peer-reviewed articles published in the Scopus database during the period of 2016 to 2021. This paper offers the identification of gaps in the literature enabling studies on the subject in higher education. The article identifies the main applications of blockchain technology in higher education around the world, as well as suggests future investigations. For further scientific investigation, we propose the operationalization of each of the researched approaches, especially combining the blockchain relationship, artificial intelligence, digital innovation, digital maturity, and customer experience in higher education.publishersversionpublishe

    To Adapt or Not to Adapt: A Quantification Technique for Measuring an Expected Degree of Self-Adaptation

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    Self-adaptation and self-organization (SASO) have been introduced to the management of technical systems as an attempt to improve robustness and administrability. In particular, both mechanisms adapt the system’s structure and behavior in response to dynamics of the environment and internal or external disturbances. By now, adaptivity has been considered to be fully desirable. This position paper argues that too much adaptation conflicts with goals such as stability and user acceptance. Consequently, a kind of situation-dependent degree of adaptation is desired, which defines the amount and severity of tolerated adaptations in certain situations. As a first step into this direction, this position paper presents a quantification approach for measuring the current adaptation behavior based on generative, probabilistic models. The behavior of this method is analyzed in terms of three application scenarios: urban traffic control, the swidden farming model, and data communication protocols. Furthermore, we define a research roadmap in terms of six challenges for an overall measurement framework for SASO systems

    Energy Usage Profiling for Virtualized Single Board Computer Clusters

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    With Network Function Virtualization (NFV) platforms gaining ground, we question the combination of NFV and Single Board Computers (SBCs) in terms of compatibility, reliability, and energy consumption. A mini cluster of SBCs is used to develop a scalable and resilient energy monitoring application. The application is employed to discover the energy demands of a NFV platform in modern SBCs, and build the energy profile of the devices and the deployed services. We use the results and the added knowledge from building the application to strengthen the argument that SBC clusters can support virtualized service deployment. This evidence, alongside the rich gamut of characteristics that SBCs hold, proves that they are a viable option for edge components of a fog network. Our results show that running different virtualised processes offers added functionality, resilience and scalability without heavily sacrificing energy consumption

    Survey of smart parking systems

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    The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.Fil: Diaz Ogás, Mathias Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Fabregat Gesa, Ramon. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

    Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications

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    [EN] In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.This work was partially supported by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00, and grant BES-2015-075988, Ayudas para contratos predoctorales 2015.Hadiwardoyo, SA.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Krinkin, K.; Klionskiy, D.; Hernández-Orallo, E.; Manzoni, P. (2020). Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications. Sensors. 20(2):1-18. https://doi.org/10.3390/s20020356S11820

    MsWH: A multi-sensory hardware platform for capturing and analyzing physiological emotional signals

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    This paper presents a new physiological signal acquisition multi-sensory platform for emotion detection: Multi-sensor Wearable Headband (MsWH). The system is capable of recording and analyzing five different physiological signals: skin temperature, blood oxygen saturation, heart rate (and its variation), movement/position of the user (more specifically of his/her head) and electrodermal activity/bioimpedance. The measurement system is complemented by a porthole camera positioned in such a way that the viewing area remains constant. Thus, the user''s face will remain centered regardless of its position and movement, increasing the accuracy of facial expression recognition algorithms. This work specifies the technical characteristics of the developed device, paying special attention to both the hardware used (sensors, conditioning, microprocessors, connections) and the software, which is optimized for accurate and massive data acquisition. Although the information can be partially processed inside the device itself, the system is capable of sending information via Wi-Fi, with a very high data transfer rate, in case external processing is required. The most important features of the developed platform have been compared with those of a proven wearable device, namely the Empatica E4 wristband, in those measurements in which this is possible
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