Sensors, Volume 15, Issue 10 (October 2015) – 139 articles , Pages 24681-27392

Most experimental fields of science and engineering require the use of data acquisition systems (DAQ), devices in charge of sampling and converting electrical signals into digital data and, typically, performing all of the required signal preconditioning. Since commercial DAQ systems are normally focused on specific types of sensors and actuators, systems engineers may need to employ mutually-incompatible hardware from different manufacturers in applications demanding heterogeneous inputs and outputs, such as small-signal analog inputs, differential quadrature rotatory encoders or variable current outputs. A common undesirable side effect of heterogeneous DAQ hardware is the lack of an accurate synchronization between samples captured by each device. To solve such a problem with low-cost hardware, we present a novel modular DAQ architecture comprising a base board and a set of interchangeable modules. Our main design goal is the ability to sample all sources at predictable, fixed sampling frequencies, with a reduced synchronization mismatch (<1 µs) between heterogeneous signal sources. We present experiments in the field of mechanical engineering, illustrating vibration spectrum analyses from piezoelectric accelerometers and, as a novelty in these kinds of experiments, the spectrum of quadrature encoder signals. Part of the design and software will be publicly released online. Full article

This paper presents a fully integrated linear Hall sensor by means of 0.8 μm high voltage complementary metal-oxide semiconductor (CMOS) technology. This monolithic Hall sensor chip features a highly sensitive horizontal switched Hall plate and an efficient signal conditioner using dynamic offset cancellation technique. An improved cross-like Hall plate achieves high magnetic sensitivity and low offset. A new spinning current modulator stabilizes the quiescent output voltage and improves the reliability of the signal conditioner. The tested results show that at the 5 V supply voltage, the maximum Hall output voltage of the monolithic Hall sensor microsystem, is up to ±2.1 V and the linearity of Hall output voltage is higher than 99% in the magnetic flux density range from ±5 mT to ±175 mT. The output equivalent residual offset is 0.48 mT and the static power consumption is 20 mW. Full article

Designing surgical instruments for robotic-assisted minimally-invasive surgery (RAMIS) is challenging due to constraints on the number and type of sensors imposed by considerations such as space or the need for sterilization. A new method for evaluating the usability of virtual teleoperated surgical instruments based on virtual sensors is presented. This method uses virtual prototyping of the surgical instrument with a dual physical interaction, which allows testing of different sensor configurations in a real environment. Moreover, the proposed approach has been applied to the evaluation of prototypes of a two-finger grasper for lump detection by remote pinching. In this example, the usability of a set of five different sensor configurations, with a different number of force sensors, is evaluated in terms of quantitative and qualitative measures in clinical experiments with 23 volunteers. As a result, the smallest number of force sensors needed in the surgical instrument that ensures the usability of the device can be determined. The details of the experimental setup are also included. Full article

Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken. Full article

Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras for simultaneous acquisition of PPGi waveform signals from the index fingertip and the forehead temple. An algorithm for the detection of maxima and minima in PPGi signals was developed, which includes technology for interpolation of the real positions of these points. We compared our PTT measurements with those obtained from the current methodological standards. Statistical results indicate that the PTT measured by our proposed method exhibits a good correlation with the established method. The proposed method is especially suitable for implementation in dual-camera-smartphones, which could facilitate PTT measurement among populations affected by cardiac complications. Full article

Traditional air quality monitoring relies on point measurements from a small number of high-end devices. The recent growth in low-cost air sensing technology stands to revolutionize the way in which air quality data are collected and utilized. While several technologies have emerged in the field of low-cost monitoring, all suffer from similar challenges in data quality. One technology that shows particular promise is that of electrolytic (also known as amperometric) sensors. These sensors produce an electric current in response to target pollutants. This work addresses the development of practical models for understanding and quantifying the signal response of electrolytic sensors. Such models compensate for confounding effects on the sensor response, such as ambient temperature and humidity, and address other issues that affect the usability of low-cost sensors, such as sensor drift and inter-sensor variability Full article

A quartz crystal microbalance (QCM) was utilized to measure the water content in ethanol. For the improvement of measurement sensitivity, the QCM was modified by applying zeolite particles on the surface with poly(methyl methacrylate) (PMMA) binder. The measurement performance was examined with ethanol of 1% to 5% water content in circulation. The experimental results showed that the frequency drop of the QCM was related with the water content though there was some deviation. The sensitivity of the zeolite-coated QCM was sufficient to be implemented in water content determination, and a higher ratio of silicon to aluminum in the molecular structure of the zeolite gave better performance. The coated surface was inspected by microscopy to show the distribution of zeolite particles and PMMA spread. Full article

The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on infrastructure such as Wi-Fi access points. To address this problem, we propose APFiLoc—a low cost, smartphone-based framework for indoor localization. The key idea behind this framework is to obtain landmarks within the environment and to use the augmented particle filter to fuse them with measurements from smartphone sensors and map information. A clustering method based on distance constraints is developed to detect organic landmarks in an unsupervised way, and the least square support vector machine is used to classify seed landmarks. A series of real-world experiments were conducted in complex environments including multiple floors and the results show APFiLoc can achieve 80% accuracy (phone in the hand) and around 70% accuracy (phone in the pocket) of the error less than 2 m error without the assistance of infrastructure like Wi-Fi access points. Full article

A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms. Full article

New guidelines and procedures for real-time (RT) network-based solutions are required in order to support Global Navigation Satellite System (GNSS) derived heights. Two kinds of experiments were carried out to analyze the performance of the network-based real-time kinematic (RTK) solutions. New test marks were installed in different surrounding environments, and the existing GPS benchmarks were used for analyzing the effect of different factors, such as baseline lengths, antenna types, on the final accuracy and reliability of the height estimation. The RT solutions are categorized into three groups: single-base RTK, multiple-epoch network RTK (mRTN), and single-epoch network RTK (sRTN). The RTK solution can be biased up to 9 mm depending on the surrounding environment, but there was no notable bias for a longer reference base station (about 30 km) In addition, the occupation time for the network RTK was investigated in various cases. There is no explicit bias in the solution for different durations, but smoother results were obtained for longer durations. Further investigation is needed into the effect of changing the occupation time between solutions and into the possibility of using single-epoch solutions in precise determination of heights by GNSS. Full article

Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype. Full article

The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials and serve as in situ sensors. In this article, embedded optical fiber Bragg grating (FBG) sensors are used to analyze the vibration characteristics of two real-life composite components. The first component is a carbon fiber-reinforced polymer automotive control arm; the second is a glass fiber-reinforced polymer aeronautic hinge arm. The modal parameters of both components were estimated by processing the FBG signals with two interrogation techniques: the maximum detection and fast phase correlation algorithms were employed for the demodulation of the FBG signals; the Peak-Picking and PolyMax techniques were instead used for the parameter estimation. To validate the FBG outcomes, reference measurements were performed by means of a laser Doppler vibrometer. The analysis of the results showed that the FBG sensing capabilities were enhanced when the recently-introduced fast phase correlation algorithm was combined with the state-of-the-art PolyMax estimator curve fitting method. In this case, the FBGs provided the most accurate results, i.e., it was possible to fully characterize the vibration behavior of both composite components. When using more traditional interrogation algorithms (maximum detection) and modal parameter estimation techniques (Peak-Picking), some of the modes were not successfully identified. Full article

Hepatitis C virus (HCV) infects hepatocytes but not dendritic cells (DCs), but DCs effectively mature in response to HCV-infected hepatocytes. Using gene-disrupted mice and hydrodynamic injection strategy, we found the MAVS pathway to be crucial for induction of type III interferons (IFNs) in response to HCV in mouse. Human hepatocytes barely express TLR3 under non-infectious states, but frequently express it in HCV infection. Type I and III IFNs are induced upon stimulation with polyI:C, an analog of double-stranded (ds)RNA. Activation of TLR3 and the TICAM-1 pathway, followed by DC-mediated activation of cellular immunity, is augmented during exposure to viral RNA. Although type III IFNs are released from replication-competent human hepatocytes, DC-mediated CTL proliferation and NK cell activation hardly occur in response to the released type III IFNs. Yet, type I IFNs and HCV-infected hepatocytes can induce maturation of DCs in either human or mouse origin. In addition, mouse CD8+ DCs mature in response to HCV-infected hepatocytes unless the TLR3/TICAM-1 pathway is blocked. We found the exosomes containing HCV RNA in the supernatant of the HCV-infected hepatocytes act as a source of TLR3-mediated DC maturation. Here we summarize our view on the mechanism by which DCs mature to induce NK and CTL in a status of HCV infection. Full article

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method. Full article

This study proposes an obstacle detection method that uses depth information to allow the visually impaired to avoid obstacles when they move in an unfamiliar environment. The system is composed of three parts: scene detection, obstacle detection and a vocal announcement. This study proposes a new method to remove the ground plane that overcomes the over-segmentation problem. This system addresses the over-segmentation problem by removing the edge and the initial seed position problem for the region growth method using the Connected Component Method (CCM). This system can detect static and dynamic obstacles. The system is simple, robust and efficient. The experimental results show that the proposed system is both robust and convenient. Full article

To minimize cargo theft during transport, mobile radio frequency identification (RFID) grouping proof methods are generally employed to ensure the integrity of entire cargo loads. However, conventional grouping proofs cannot simultaneously generate grouping proofs for a specific group of RFID tags. The most serious problem of these methods is that nonexistent tags are included in the grouping proofs because of the considerable amount of time it takes to scan a high number of tags. Thus, applying grouping proof methods in the current logistics industry is difficult. To solve this problem, this paper proposes a method for generating multilayered offline grouping proofs. The proposed method provides tag anonymity; moreover, resolving disputes between recipients and transporters over the integrity of cargo deliveries can be expedited by generating grouping proofs and automatically authenticating the consistency between the receipt proof and pick proof. The proposed method can also protect against replay attacks, multi-session attacks, and concurrency attacks. Finally, experimental results verify that, compared with other methods for generating grouping proofs, the proposed method can efficiently generate offline grouping proofs involving several parties in a supply chain using mobile RFID. Full article

Target positioning systems based on MEMS gyros and laser rangefinders (LRs) have extensive prospects due to their advantages of low cost, small size and easy realization. The target positioning accuracy is mainly determined by the LR’s attitude derived by the gyros. However, the attitude error is large due to the inherent noises from isolated MEMS gyros. In this paper, both accelerometer/magnetometer and LR attitude aiding systems are introduced to aid MEMS gyros. A no-reset Federated Kalman Filter (FKF) is employed, which consists of two local Kalman Filters (KF) and a Master Filter (MF). The local KFs are designed by using the Direction Cosine Matrix (DCM)-based dynamic equations and the measurements from the two aiding systems. The KFs can estimate the attitude simultaneously to limit the attitude errors resulting from the gyros. Then, the MF fuses the redundant attitude estimates to yield globally optimal estimates. Simulation and experimental results demonstrate that the FKF-based system can improve the target positioning accuracy effectively and allow for good fault-tolerant capability. Full article

A methanol microsensor integrated with a micro heater manufactured using the complementary metal oxide semiconductor (CMOS)-microelectromechanical system (MEMS) technique was presented. The sensor has a capability of detecting low concentration methanol gas. Structure of the sensor is composed of interdigitated electrodes, a sensitive film and a heater. The heater located under the interdigitated electrodes is utilized to provide a working temperature to the sensitive film. The sensitive film prepared by the sol-gel method is tin dioxide doped cadmium sulfide, which is deposited on the interdigitated electrodes. To obtain the suspended structure and deposit the sensitive film, the sensor needs a post-CMOS process to etch the sacrificial silicon dioxide layer and silicon substrate. The methanol senor is a resistive type. A readout circuit converts the resistance variation of the sensor into the output voltage. The experimental results show that the methanol sensor has a sensitivity of 0.18 V/ppm. Full article

We report the results of composite tungsten oxide nanowires-based gas sensors. The morphologic surface, crystallographic structures, and chemical compositions of the obtained nanowires have been investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman scattering, respectively. The experimental measurements reveal that each wire consists of crystalline nanoparticles with an average diameter of less than 250 nm. By using the synthesized nanowires, highly sensitive prototypic gas sensors have been designed and fabricated. The dependence of the sensitivity of tungsten oxide nanowires to the methane and hydrogen gases as a function of time has been obtained. Various sensing parameters such as sensitivity, response time, stability, and repeatability were investigated in order to reveal the sensing ability. Full article

In order to study the sulfidation of a catalyst fixed bed, an in operando single pellet sensor was designed. A catalyst pellet from the fixed bed was electrically contacted and its electrical response was correlated with the catalyst behavior. For the sulfidation tests, a nickel catalyst was used and was sulfidized with H₂S. This catalyst had a very low conductivity in the reduced state. During sulfidation, the conductivity of the catalyst increased by decades. A reaction from nickel to nickel sulfide occurred. This conductivity increase by decades during sulfidation had not been expected since both nickel and nickel sulfides behave metallic. Only by assuming a percolation phenomenon that originates from a volume increase of the nickel contacts when reacting to nickel sulfides, this effect can be explained. This assumption was supported by sulfidation tests with differently nickel loaded catalysts and it was quantitatively estimated by a general effective media theory. The single pellet sensor device for in operando investigation of sulfidation can be considered as a valuable tool to get further insights into catalysts under reaction conditions. Full article

The demountable disk-drum aero-engine rotor is an important piece of equipment that greatly impacts the safe operation of aircraft. However, assembly looseness or crack fault has led to several unscheduled breakdowns and serious accidents. Thus, condition monitoring and fault diagnosis technique are required for identifying abnormal conditions. Customized ensemble multiwavelet method for aero-engine rotor condition identification, using measured vibration data, is developed in this paper. First, customized multiwavelet basis function with strong adaptivity is constructed via symmetric multiwavelet lifting scheme. Then vibration signal is processed by customized ensemble multiwavelet transform. Next, normalized information entropy of multiwavelet decomposition coefficients is computed to directly reflect and evaluate the condition. The proposed approach is first applied to fault detection of an experimental aero-engine rotor. Finally, the proposed approach is used in an engineering application, where it successfully identified the crack fault of a demountable disk-drum aero-engine rotor. The results show that the proposed method possesses excellent performance in fault detection of aero-engine rotor. Moreover, the robustness of the multiwavelet method against noise is also tested and verified by simulation and field experiments. Full article

Chronic obstructive pulmonary disease (COPD) is one of the commonest causes of death in the world and poses a substantial burden on healthcare systems and patients’ quality of life. The largest component of the related healthcare costs is attributable to admissions due to acute exacerbation (AECOPD). The evidence that might support the effectiveness of the telemonitoring interventions in COPD is limited partially due to the lack of useful predictors for the early detection of AECOPD. Electronic stethoscopes and computerised analyses of respiratory sounds (CARS) techniques provide an opportunity for substantial improvement in the management of respiratory diseases. This exploratory study aimed to evaluate the feasibility of using: (a) a respiratory sensor embedded in a self-tailored housing for ageing users; (b) a telehealth framework; (c) CARS and (d) machine learning techniques for the remote early detection of the AECOPD. In a 6-month pilot study, 16 patients with COPD were equipped with a home base-station and a sensor to daily record their respiratory sounds. Principal component analysis (PCA) and a support vector machine (SVM) classifier was designed to predict AECOPD. 75.8% exacerbations were early detected with an average of 5 ± 1.9 days in advance at medical attention. The proposed method could provide support to patients, physicians and healthcare systems. Full article

Ultrasonic concentration meters have widely been used at water purification, sewage treatment and waste water treatment plants to sort and transfer high concentration sludges and to control the amount of chemical dosage. When an unusual substance is contained in the sludge, however, the attenuation of ultrasonic waves could be increased or not be transmitted to the receiver. In this case, the value measured by a concentration meter is higher than the actual density value or vibration. As well, it is difficult to automate the residuals treatment process according to the various problems such as sludge attachment or sensor failure. An ultrasonic multi-beam concentration sensor was considered to solve these problems, but an abnormal concentration value of a specific ultrasonic beam degrades the accuracy of the entire measurement in case of using a conventional arithmetic mean for all measurement values, so this paper proposes a method to improve the accuracy of the sludge concentration determination by choosing reliable sensor values and applying a neuro-fuzzy learning algorithm. The newly developed meter is proven to render useful results from a variety of experiments on a real water treatment plant. Full article

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. Full article

A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors. Full article

We describe a sensitive plant monitoring system by the detection of the bioelectric potentials in plants with boron-doped diamond (BDD) electrodes. For sensor electrodes, we used commercially available BDD, Ag, and Pt plate electrodes. We tested this approach on a hybrid species in the genus Opuntia (potted) and three different trees (ground-planted) at different places in Japan. For the Opuntia, we artificially induced bioelectric potential changes by the surface potential using the fingers. We detected substantial changes in bioelectric potentials through all electrodes during finger touches on the surface of potted Opuntia hybrid plants, although the BDD electrodes were several times more sensitive to bioelectric potential change compared to the other electrodes. Similarly for ground-planted trees, we found that both BDD and Pt electrodes detected bioelectric potential change induced by changing environmental factors (temperature and humidity) for months without replacing/removing/changing electrodes, BDD electrodes were 5–10 times more sensitive in this detection than Pt electrodes. Given these results, we conclude that BDD electrodes on live plant tissue were able to consistently detect bioelectrical potential changes in plants. Full article

In this research, we develop a micro-engineered conductive elastomeric electrode for measurements of human bio-potentials with the absence of conductive pastes. Mixing the biocompatible polydimethylsiloxane (PDMS) silicone with other biocompatible conductive nano-particles further provides the material with an electrical conductivity. We apply micro-replica mold casting for the micro-structures, which are arrays of micro-pillars embedded between two bulk conductive-PDMS layers. These micro-structures can reduce the micro-structural deformations along the direction of signal transmission; therefore the corresponding electrical impedance under the physical stretch by the movement of the human body can be maintained. Additionally, we conduct experiments to compare the electrical properties between the bulk conductive-PDMS material and the microengineered electrodes under stretch. We also demonstrate the working performance of these micro-engineered electrodes in the acquisition of the 12-lead electrocardiographs (ECG) of a healthy subject. Together, the presented gel-less microengineered electrodes can provide a more convenient and stable bio-potential measurement platform, making tele-medical care more achievable with reduced technical barriers for instrument installation performed by patients/users themselves. Full article

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. Full article

Commercially available Pt screen printed electrodes (SPEs) have been employed as possible electrode materials for methylamine (MA) and hydrogen chloride (HCl) gas detection. The room temperature ionic liquid (RTIL) 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C₂mim][NTf₂]) was used as a solvent and the electrochemical behaviour of both gases was first examined using cyclic voltammetry. The reaction mechanism appears to be the same on Pt SPEs as on Pt microelectrodes. Furthermore, the analytical utility was studied to understand the behaviour of these highly toxic gases at low concentrations on SPEs, with calibration graphs obtained from 10 to 80 ppm. Three different electrochemical techniques were employed: linear sweep voltammetry (LSV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV), with no significant differences in the limits of detection (LODs) between the techniques (LODs were between 1.4 to 3.6 ppm for all three techniques for both gases). The LODs achieved on Pt SPEs were lower than the current Occupational Safety and Health Administration Permissible Exposure Limit (OSHA PEL) limits of the two gases (5 ppm for HCl and 10 ppm for MA), suggesting that Pt SPEs can successfully be combined with RTILs to be used as cheap alternatives for amperometric gas sensing in applications where these toxic gases may be released. Full article

Entropy in computer security is associated with the unpredictability of a source of randomness. The random source with high entropy tends to achieve a uniform distribution of random values. Random number generators are one of the most important building blocks of cryptosystems. In constrained devices of the Internet of Things ecosystem, high entropy random number generators are hard to achieve due to hardware limitations. For the purpose of the random number generation in constrained devices, this work proposes a solution based on the least-significant bits concatenation entropy harvesting method. As a potential source of entropy, on-board integrated sensors (i.e., temperature, humidity and two different light sensors) have been analyzed. Additionally, the costs (i.e., time and memory consumption) of the presented approach have been measured. The results obtained from the proposed method with statistical fine tuning achieved a Shannon entropy of around 7.9 bits per byte of data for temperature and humidity sensors. The results showed that sensor-based random number generators are a valuable source of entropy with very small RAM and Flash memory requirements for constrained devices of the Internet of Things. Full article