BlueSense: designing an extensible platform for wearable motion sensing, sensor research and IoT applications

We present an extensible sensor research platform for wearable and IoT applications. The result is a 30x30mm platform capable of 500Hz motion and orientation sensing using 98mW when logging the data. The platform can wake up at programmed intervals using only 70uW in hardware off mode. A maximum 0.6ppm time deviation between nodes allows usage in a network for whole body movement sensing

Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing

Smart city sensing calls for crowdsensing via mobile devices that are equipped with various built-in sensors. As incentivizing users to participate in distributed sensing is still an open research issue, the trustworthiness of crowdsensed data is expected to be a grand challenge if this cloud-inspired recruitment of sensing services is to be adopted. Recent research proposes reputation-based user recruitment models for crowdsensing; however, there is no standard way of identifying adversaries in smart city crowdsensing. This paper adopts previously proposed vote-based approaches, and presents a thorough performance study of vote-based trustworthiness with trusted entities that are basically a subset of the participating smartphone users. Those entities are called trustworthy anchors of the crowdsensing system. Thus, an anchor user is fully trustworthy and is fully capable of voting for the trustworthiness of other users, who participate in sensing of the same set of phenomena. Besides the anchors, the reputations of regular users are determined based on vote-based (distributed) reputation. We present a detailed performance study of the anchor-based trustworthiness assurance in smart city crowdsensing through simulations, and compare it with the purely vote-based trustworthiness approach without anchors, and a reputation-unaware crowdsensing approach, where user reputations are discarded. Through simulation findings, we aim at providing specifications regarding the impact of anchor and adversary populations on crowdsensing and user utilities under various environmental settings. We show that significant improvement can be achieved in terms of usefulness and trustworthiness of the crowdsensed data if the size of the anchor population is set properl

Quantifying User Reputation Scores, Data Trustworthiness, and User Incentives in Mobile Crowd-Sensing

Ubiquity of mobile devices with rich sensory capabilities has given rise to the mobile crowd-sensing (MCS) concept, in which a central authority (the platform) and its participants (mobile users) work collaboratively to acquire sensory data over a wide geographic area. Recent research in MCS highlights the following facts: 1) a utility metric can be defined for both the platform and the users, quantifying the value received by either side; 2) incentivizing the users to participate is a non-trivial challenge; 3) correctness and truthfulness of the acquired data must be verified, because the users might provide incorrect or inaccurate data, whether due to malicious intent or malfunctioning devices; and 4) an intricate relationship exists among platform utility, user utility, user reputation, and data trustworthiness, suggesting a co-quantification of these inter-related metrics. In this paper, we study two existing approaches that quantify crowd-sensed data trustworthiness, based on statistical and vote-based user reputation scores. We introduce a new metric - collaborative reputation scores - to expand this definition. Our simulation results show that collaborative reputation scores can provide an effective alternative to the previously proposed metrics and are able to extend crowd sensing to applications that are driven by a centralized as well as decentralized control

Mixing instabilities during shearing of metals

Severe plastic deformation of solids is relevant to many materials processing techniques as well as tribological events such as wear. It results in microstructural refinement, redistribution of phases, and ultimately even mixing. However, mostly due to inability to experimentally capture the dynamics of deformation, the underlying physical mechanisms remain elusive. Here, we introduce a strategy that reveals details of morphological evolution upon shearing up to ultrahigh strains. Our experiments on metallic multilayers find that mechanically stronger layers either fold in a quasi-regular manner and subsequently evolve into periodic vortices, or delaminate into finer layers before mixing takes place. Numerical simulations performed by treating the phases as nonlinear viscous fluids reproduce the experimental findings and reveal the origin for emergence of a wealth of morphologies in deforming solids. They show that the same instability that causes kilometer-thick rock layers to fold on geological timescales is acting here at micrometer level

Flexible IGZO TFT Spice model and design of active strain-compensation circuits for bendable active matrix arrays

The detailed measurement and characterization of strain induced performance variations in flexible InGaZnO thinfilm transistors (TFTs) resulted in a Spice TFT model able to simulate tensile and compressive bending. This model was used to evaluate a new concept, namely the active compensation of strain induced performance variations in pixel driving circuits for bendable active matrix arrays. The designed circuits can compensate the mobility and threshold voltage shifts in IGZO TFTs induced by bending. In a single TFT, a drain current of 1 mA varies by 83 µA per percent of mechanical strain. The most effective compensation circuit design, comprising one additional TFT and two resistors, reduces the driving current variation to 1.1 µA per percent of strain. The compensation circuit requires no additional control signals, and increases the power consumption by only 235 µW (corresponds to 4.7 %). Finally, switching operation is possible for frequencies up to 200 kHz. This opens a way towards the fabrication of flexible displays with constant brightness even when bent

Low temperature and radiation stability of flexible IGZO TFTs and their suitability for space applications

In this paper, Low Earth Orbit radiation and temperature conditions are mimicked to investigate the suitability of flexible Indium-Gallium-Zinc-Oxide transistors for lightweight space-wearables. Such wearable devices could be incorporated into spacesuits as unobtrusive sensors such as radiation detectors or physiological monitors. Due to the harsh environment to which these space-wearables would be exposed, they have to be able to withstand high radiation doses and low temperatures. For this reason, the impacts of high energetic electron irradiation with fluences up to 1012 e-/cm2 and low operating temperatures down to 78 K, are investigated. This simulates 278 h in a Low Earth Orbit. The threshold voltage and mobility of transistors that were exposed to e- irradiation are found to shift by +0.09 ± 0.05V and -0.6 ± 0.5cm2 V-1 s-1. Subsequent low temperature exposure resulted in additional shifts of +0.38 V and -5.95 cm2 V-1 s-1 for the same parameters. These values are larger than the ones obtained from non-irradiated reference samples. If this is considered during the systems’ design, these devices can be used to unobtrusively integrate sensor systems into space-suits

Flexible temperature sensor integration into e-textiles using different industrial yarn fabrication processes

Textiles enhanced with thin-film flexible sensors are well-suited for unobtrusive monitoring of skin parameters due to the sensors’ high conformability. These sensors can be damaged if they are attached to the surface of the textile, also affecting the textiles’ aesthetics and feel. We investigate the effect of embedding flexible temperature sensors within textile yarns, which adds a layer of protection to the sensor. Industrial yarn manufacturing techniques including knit braiding, braiding, and double covering were utilised to identify an appropriate incorporation technique. The thermal time constants recorded by all three sensing yarns was <10 s. Simultaneously, effective sensitivity only decreased by a maximum of 14% compared to the uncovered sensor. This is due to the sensor being positioned within the yarn instead of being in direct contact with the measured surface. These sensor yarns were not affected by bending and produced repeatable measurements. The double covering method was observed to have the least impact on the sensors’ performance due to the yarn’s smaller dimensions. Finally, a sensing yarn was incorporated in an armband and used to measure changes in skin temperature. The demonstrated textile integration techniques for flexible sensors using industrial yarn manufacturing processes enable large-scale smart textile fabrication

Game-Theoretic Recruitment of Sensing Service Providers for Trustworthy Cloud-Centric Internet-of-Things (IoT) Applications

Widespread use of connected smart devices that are equipped with various built-in sensors has introduced the mobile crowdsensing concept to the IoT-driven information and communication applications. Mobile crowdsensing requires implicit collaboration between the crowdsourcer/recruiter platforms and users. Additionally, users need to be incentivized by the crowdsensing platform because each party aims to maximize their utility. Due to the participatory nature of data collection, trustworthiness and truthfulness pose a grand challenge in crowdsensing systems in the presence of malicious users, who either aim to manipulate sensed data or collaborate unfaithfully with the motivation of maximizing their income. In this paper, we propose a game-theoretic approach for trustworthiness-driven user recruitment in mobile crowdsensing systems that consists of three phases: i) user recruitment, ii) collaborative decision making on trust scores, and iii) badge rewarding. Our proposed framework incentivizes the users through a sub-game perfect equilibrium (SPE) and gamification techniques. Through simulations, we show that the platform utility can be improved by up to the order of 50\% while the average user utility can be increased by at least 15\% when compared to fully-distributed and user-centric trustworthy crowdsensing

Biocompatible gel-free coconut-oil and carbon black electrodes for ECG and respiration measurements

The current state of the art in telemedicine has increased the interest in long term monitoring of physiological and bioelectric signals. This motivated the development of materials and techniques for the fabrication of biocompatible, user and environmentally friendly alternatives to conventional resistive wet electrodes. Here we report a method for the fabrication of dry flexible and stretchable electrodes based on Coconut-Oil and Carbon Black for the monitoring of electrophysiological signals without conductive gels. The highly stretchable material shows a specific resistance ρ down to 33.2±12.3Ωm, high conformability, and a stretchability up to 1500%. The epidermal electrodes were used to record Electrocardiographic (ECG) signals and measure respiration in a 3-lead configuration and compared to commercial wet electrodes. Even after being elongated by 100% for 100 stretch/release cycles, a reliable recording of the QRS-complex is demonstrated without the need for any contact enhancer or substances that cause skin reaction, demonstrating the potential use of this material for long term ECG monitoring applications

Design and characterisation of a non-contact flexible sensor array for electric potential imaging applications

Capacitive non-contact imaging of electric fields and potentials with micro-metre resolution can provide relevant insights into material characterisation, structural analysis, electrostatic charge imaging and bio-sensing applications. However, scanning electric potential microscopes have been confined to rigid and single-probe devices, making them slow, prone to mechanical damage and complex to fabricate. In this work, we present the design and characterisation of a novel 5-element flexible array of electric potential probes with spatial resolution down to 20μm to speed up the scanning time. This was achieved by combining flexible thin-film probes for active guarding and shielding with state-of-the art discrete conditioning circuits. The potential of this approach is showcased by using the fabricated array to image latent fingerprints deposited on an insulating surface by contact electrification, obtain the surface topography of conductive samples and to visualise local dielectric variations