889 research outputs found

    The passive operating mode of the linear optical gesture sensor

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    The study evaluates the influence of natural light conditions on the effectiveness of the linear optical gesture sensor, working in the presence of ambient light only (passive mode). The orientations of the device in reference to the light source were modified in order to verify the sensitivity of the sensor. A criterion for the differentiation between two states: "possible gesture" and "no gesture" was proposed. Additionally, different light conditions and possible features were investigated, relevant for the decision of switching between the passive and active modes of the device. The criterion was evaluated based on the specificity and sensitivity analysis of the binary ambient light condition classifier. The elaborated classifier predicts ambient light conditions with the accuracy of 85.15%. Understanding the light conditions, the hand pose can be detected. The achieved accuracy of the hand poses classifier trained on the data obtained in the passive mode in favorable light conditions was 98.76%. It was also shown that the passive operating mode of the linear gesture sensor reduces the total energy consumption by 93.34%, resulting in 0.132 mA. It was concluded that optical linear sensor could be efficiently used in various lighting conditions.Comment: 10 pages, 14 figure

    Gait Recognition as a Service for Unobtrusive User Identification in Smart Spaces

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    Recently, Internet of Things (IoT) has raised as an important research area that combines the environmental sensing and machine learning capabilities to flourish the concept of smart spaces, in which intelligent and customized services can be provided to users in a smart manner. In smart spaces, one fundamental service that needs to be provided is accurate and unobtrusive user identification. In this work, to address this challenge, we propose a Gait Recognition as a Service (GRaaS) model, which is an instantiation of the traditional Sensing as a Service (S2aaS) model, and is specially deigned for user identification using gait in smart spaces. To illustrate the idea, a Radio Frequency Identification (RFID)-based gait recognition service is designed and implemented following the GRaaS concept. Novel tag selection algorithms and attention-based Long Short-term Memory (At-LSTM) models are designed to realize the device layer and edge layer, achieving a robust recognition with 96.3% accuracy. Extensive evaluations are provided, which show that the proposed service has accurate and robust performance and has great potential to support future smart space applications

    Clothing-Integrated Human-Technology Interaction

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    Due to the different disabilities of people and versatile use environments, the current handheld and screen-based digital devices on the market are not suitable for all consumers and all situations. Thus, there is an urgent need for human- technology interaction solutions, where the required input actions to digital devices are simple, easy to establish, and instinctive, allowing the whole society to effortlessly interact with the surrounding technology. In passive ultra-high frequency (UHF) radio frequency identification (RFID) systems, the tag consists only of an antenna and a simple integrated circuit (IC). The tag gets all the needed power from the RFID reader and can be thus seamlessly and in a maintenance-free way integrated into clothing. In this thesis, it is presented that by integrating passive UHF RFID technology into clothing, body movements and gestures can be monitored by monitoring the individual IDs and backscattered signals of the tags. Electro-textiles and embroidery with conductive thread are found to be suitable options when manufacturing and materials for such garments are considered. This thesis establishes several RFID- based interface solutions, multiple types of inputs through RFID platforms, and controlling the surrounding and communicating with RFID-based on/off functions. The developed intelligent clothing is visioned to provide versatile applications for assistive technology, for entertainment, and ambient assistant living, and for comfort and safety in work environments, just to name a few examples

    Central monitoring system for ambient assisted living

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    Smart homes for aged care enable the elderly to stay in their own homes longer. By means of various types of ambient and wearable sensors information is gathered on people living in smart homes for aged care. This information is then processed to determine the activities of daily living (ADL) and provide vital information to carers. Many examples of smart homes for aged care can be found in literature, however, little or no evidence can be found with respect to interoperability of various sensors and devices along with associated functions. One key element with respect to interoperability is the central monitoring system in a smart home. This thesis analyses and presents key functions and requirements of a central monitoring system. The outcomes of this thesis may benefit developers of smart homes for aged care

    Survey and Systematization of Secure Device Pairing

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    Secure Device Pairing (SDP) schemes have been developed to facilitate secure communications among smart devices, both personal mobile devices and Internet of Things (IoT) devices. Comparison and assessment of SDP schemes is troublesome, because each scheme makes different assumptions about out-of-band channels and adversary models, and are driven by their particular use-cases. A conceptual model that facilitates meaningful comparison among SDP schemes is missing. We provide such a model. In this article, we survey and analyze a wide range of SDP schemes that are described in the literature, including a number that have been adopted as standards. A system model and consistent terminology for SDP schemes are built on the foundation of this survey, which are then used to classify existing SDP schemes into a taxonomy that, for the first time, enables their meaningful comparison and analysis.The existing SDP schemes are analyzed using this model, revealing common systemic security weaknesses among the surveyed SDP schemes that should become priority areas for future SDP research, such as improving the integration of privacy requirements into the design of SDP schemes. Our results allow SDP scheme designers to create schemes that are more easily comparable with one another, and to assist the prevention of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications Surveys & Tutorials 2017 (Volume: PP, Issue: 99

    WristFlex: low-power gesture input with wrist-worn pressure sensors

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    In this paper we present WristFlex, an always-available on-body gestural interface. Using an array of force sensitive resistors (FSRs) worn around the wrist, the interface can distinguish subtle finger pinch gestures with high accuracy (>80 %) and speed. The system is trained to classify gestures from subtle tendon movements on the wrist. We demonstrate that WristFlex is a complete system that works wirelessly in real-time. The system is simple and light-weight in terms of power consumption and computational overhead. WristFlex's sensor power consumption is 60.7 uW, allowing the prototype to potentially last more then a week on a small lithium polymer battery. Also, WristFlex is small and non-obtrusive, and can be integrated into a wristwatch or a bracelet. We perform user studies to evaluate the accuracy, speed, and repeatability. We demonstrate that the number of gestures can be extended with orientation data from an accelerometer. We conclude by showing example applications.National Science Foundation (U.S.) (NSF award 1256082
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