Sensors, Volume 18, Issue 6 (June 2018) – 312 articles

Recently, image-filtering based hyperspectral image (HSI) feature extraction has been widely studied. However, due to limited spatial resolution and feature distribution complexity, the problems of cross-region mixing after filtering and spectral discriminative reduction still remain. To address these issues, this paper proposes a spectral-spatial propagation filter (PF) based HSI feature extraction method that can effectively address the above problems. The dimensionality/band of an HSI is typically high; therefore, principal component analysis (PCA) is first used to reduce the HSI dimensionality. Then, the principal components of the HSI are filtered with the PF. When cross-region mixture occurs in the image, the filter template reduces the weight assignments of the cross-region mixed pixels to handle the issue of cross-region mixed pixels simply and effectively. To validate the effectiveness of the proposed method, experiments are carried out on three common HSIs using support vector machine (SVM) classifiers with features learned by the PF. The experimental results demonstrate that the proposed method effectively extracts the spectral-spatial features of HSIs and significantly improves the accuracy of HSI classification. Full article

Due to the great influence of multipath effect, noise, clock and error on pseudorange, the carrier phase double difference equation is widely used in high-precision indoor pseudolite positioning. The initial position is determined mostly by the known point initialization (KPI) method, and then the ambiguities can be fixed with the LAMBDA method. In this paper, a new method without using the KPI to achieve high-precision indoor pseudolite positioning is proposed. The initial coordinates can be quickly obtained to meet the accuracy requirement of the indoor LAMBDA method. The detailed processes of the method follows: Aiming at the low-cost single-frequency pseudolite system, the static differential pseudolite system (DPL) method is used to obtain the low-accuracy positioning coordinates of the rover station quickly. Then, the ambiguity function method (AFM) is used to search for the coordinates in the corresponding epoch. The real coordinates obtained by AFM can meet the initial accuracy requirement of the LAMBDA method, so that the double difference carrier phase ambiguities can be correctly fixed. Following the above steps, high-precision indoor pseudolite positioning can be realized. Several experiments, including static and dynamic tests, are conducted to verify the feasibility of the new method. According to the results of the experiments, the initial coordinates with the accuracy of decimeter level through the DPL can be obtained. For the AFM part, both a one-meter search scope and two-centimeter or four-centimeter search steps are used to ensure the precision at the centimeter level and high search efficiency. After dealing with the problem of multiple peaks caused by the ambiguity cosine function, the coordinate information of the maximum ambiguity function value (AFV) is taken as the initial value of the LAMBDA, and the ambiguities can be fixed quickly. The new method provides accuracies at the centimeter level for dynamic experiments and at the millimeter level for static ones. Full article

A cost-effective approach to gather information in a smart city is to embed sensors in vehicles such as buses. To understand the limitations and opportunities of this model, it is fundamental to investigate the spatial coverage of such a network, especially in the case where only a subset of the buses have a sensing device embedded. In this paper, we propose a model to select the right subset of buses that maximizes the coverage of the city. We evaluate the model in a real scenario based on a large-scale dataset of more than 5700 buses in the city of Rio de Janeiro, Brazil. Among other findings, we observe that the fleet of buses covers approximately 5655 km of streets (approximately 47% of the streets) and show that it is possible to cover 94% of the same streets if only 18% of buses have sensing capabilities embedded. Full article

Extrinsic Fabry–Perot (FP) interferometric sensors are being intensively applied for partial discharge (PD) detection and localization. Previous research work has mainly focused on novel structures and materials to improve the sensitivity and linear response of these sensors. However, the directional response behavior of an FP ultrasonic sensor is also of particular importance in localizing the PD source, which is rarely considered. Here, the directional sensitivity of a microelectromechanical system (MEMS)-based FP ultrasonic sensor with a 5-μm-thick micromechanical vibrating diaphragm is experimentally investigated. Ultrasonic signals from a discharge source with varying incident angles and linear distances are measured and analyzed. The results show that the sensor has a 5.90 dB amplitude fluctuation over a ±60° incident range and an exciting capability to detect weak PD signals from 3 m away due to its high signal–noise ratio. The findings are expected to optimize the configuration of a sensor array and accurately localize the PD source. Full article

Indoor positioning is in high demand in a variety of applications, and indoor environment is a challenging scene for visual positioning. This paper proposes an accurate visual positioning method for smartphones. The proposed method includes three procedures. First, an indoor high-precision 3D photorealistic map is produced using a mobile mapping system, and the intrinsic and extrinsic parameters of the images are obtained from the mapping result. A point cloud is calculated using feature matching and multi-view forward intersection. Second, top-K similar images are queried using hamming embedding with SIFT feature description. Feature matching and pose voting are used to select correctly matched image, and the relationship between image points and 3D points is obtained. Finally, outlier points are removed using P3P with the coarse focal length. Perspective-four-point with unknown focal length and random sample consensus are used to calculate the intrinsic and extrinsic parameters of the query image and then to obtain the positioning of the smartphone. Compared with established baseline methods, the proposed method is more accurate and reliable. The experiment results show that 70 percent of the images achieve location error smaller than 0.9 m in a 10 m × 15.8 m room, and the prospect of improvement is discussed. Full article

This study investigates the superiority of cooperative broadcast transmission over traditional orthogonal schemes when applied in a downlink relaying broadcast channel (RBC). Two proposed cooperative broadcast transmission protocols, one with an amplify-and-forward (AF) relay, and the other with a repetition-based decode-and-forward (DF) relay, are investigated. By utilizing superposition coding (SupC), the source and the relay transmit the private user messages simultaneously instead of sequentially as in traditional orthogonal schemes, which means the channel resources are reused and an increased channel degree of freedom is available to each user, hence the half-duplex penalty of relaying is alleviated. To facilitate a performance evaluation, theoretical outage probability expressions of the two broadcast transmission schemes are developed, based on which, we investigate the minimum total power consumption of each scheme for a given traffic requirement by numerical simulation. The results provide details on the overall system performance and fruitful insights on the essential characteristics of cooperative broadcast transmission in RBCs. It is observed that better overall outage performances and considerable power gains can be obtained by utilizing cooperative broadcast transmissions compared to traditional orthogonal schemes. Full article

To solve the intractable problems of optimal rank truncation threshold and dominant modes selection strategy of the standard dynamic mode decomposition (DMD), an improved DMD algorithm is introduced in this paper. Distinct from the conventional methods, a convex optimization framework is introduced by applying a parameterized non-convex penalty function to obtain the optimal rank truncation number. This method is inspirited by the performance that it is more perfectible than other rank truncation methods in inhibiting noise disturbance. A hierarchical and multiresolution application similar to the process of wavelet packet decomposition in modes selection is presented so as to improve the algorithm’s performance. With the modes selection strategy, the frequency spectrum of the reconstruction signal is more readable and interference-free. The improved DMD algorithm successfully extracts the fault characteristics of rolling bearing fault signals when it is utilized for mechanical signal feature extraction. Results demonstrated that the proposed method has good application prospects in denoising and fault feature extraction for mechanical signals. Full article

Ultrasonic transmission measurements have been used for decades to monitor concrete elements, mostly on a laboratory scale. Recently, coda wave interferometry (CWI), a technique adapted from seismology, was introduced to civil engineering experiments. It can be used to reveal subtle changes in concrete laboratory samples and even large structural elements without having a transducer directly at the place where the change is taking place. Here, several load tests until failure on large posttensioned concrete beams have been monitored using networks of embedded transducers. To detect subtle effects at the beginning of the experiments and cope with severe changes due to cracking close to failure, the coda wave interferometry procedures had to be modified to an adapted step-wise approach. Using this methodology, we were able to monitor stress distribution and localize large cracks by a relatively simple technique. Implementation of this approach on selected real structures might help to make decisions in infrastructure asset management. Full article

Pedestrian dead reckoning (PDR) using smart phone-embedded micro-electro-mechanical system (MEMS) sensors plays a key role in ubiquitous localization indoors and outdoors. However, as a relative localization method, it suffers from the problem of error accumulation which prevents it from long term independent running. Heading estimation error is one of the main location error sources, and therefore, in order to improve the location tracking performance of the PDR method in complex environments, an approach based on robust adaptive Kalman filtering (RAKF) for estimating accurate headings is proposed. In our approach, outputs from gyroscope, accelerometer, and magnetometer sensors are fused using the solution of Kalman filtering (KF) that the heading measurements derived from accelerations and magnetic field data are used to correct the states integrated from angular rates. In order to identify and control measurement outliers, a maximum likelihood-type estimator (M-estimator)-based model is used. Moreover, an adaptive factor is applied to resist the negative effects of state model disturbances. Extensive experiments under static and dynamic conditions were conducted in indoor environments. The experimental results demonstrate the proposed approach provides more accurate heading estimates and supports more robust and dynamic adaptive location tracking, compared with methods based on conventional KF. Full article

This paper proposes a cooperative medium access control (MAC) protocol for underwater wireless sensor networks (UWSNs) named UCMAC, which fundamentally benefits from cooperative communication. In UCMAC, a source identifies cooperators and provides its destination with a list of the cooperators while also delineating their proximity to the destination. For erroneous reception of data packets, the destination then requests retransmission to the cooperators in a closest-one-first manner. A designated cooperator transmits the buffered data packet it has successfully overheard from the source or other cooperators. A signaling procedure and the various waiting times of the nodes are carefully designed to address the overheads that stem from cooperation. Through computer simulation, this paper evaluates UCMAC in terms of system throughput, latency, single-hop packet delivery ratio (PDR), and energy efficiency. The results show that UCMAC performs better than existing schemes, including MACA-U and CD-MACA. Full article

The Fiber Bragg Grating (FBG) sensing technique is suitable for a wide variety of measurements, including temperature, pressure, acceleration, liquid level, etc., and has been applied to many bridges and buildings in the past two decades. The fact that the FBG technique can only monitor and measure strain data for most cases when it is used for deformation measurements impedes application of the FBG sensing technique in civil infrastructures. This paper proposes FBG sensing-based deformation monitoring methods that are applicable to monitoring beam deflection, column inclination angle and mortise-tenon joint dislocation for Chinese traditional timber structures. On the basis of improved conjugated beam theory and geometrical trigonometric function relationship, the relationships between the FBG sensing strain values and the deflection of beam, inclination angle of column, as well as the amount of dislocation of mortise-tenon joint are deducted for Chinese traditional buildings. A series of experiments were conducted to verify the applicability and effectiveness of the proposed deformation monitoring methods. The results show that a good agreement is obtained between the values given by the methods proposed in this paper and other methods. This implies that the proposed deformation monitoring methods are applicable and effective in the health monitoring of Chinese traditional timber structures. Full article

Various measurement monitoring techniques are investigated to mitigate the effect of global navigation satellite systems (GNSS) code multipath through error correction, stochastic weighting of measurements and detection and exclusion (or de-weighting) of affected measurements. Following a comprehensive review of each approach, the paper focuses on detection/exclusion and detection/de-weighting techniques where several single and dual-frequency monitoring metrics are employed in a combination with time-averaging and the M of N detection strategy. A new Geometry-Free (GF) detection metric is proposed given its capability to be combined with a preceding Code-Minus-Carrier (CMC)-based error correction to reduce the number of excluded or de-weighted measurements and thus preserve the measurement geometry. Three geometry-based algorithms, namely measurement subset testing, consecutive exclusion and iterative change of measurement weights are investigated to address multipath scenarios with multiple simultaneously affected measurements. Experimental results are provided using GPS L1, L2C and L5 data collected in multipath environments for static and kinematic scenarios. For GPS L1, the proposed combined method shows more than 38% improvement over a conventional Carrier-to-Noise-density ratio (C/N₀)-based Least-Squares (LS) solution in all but deep urban canyons. Lower performance was observed for L2C and L5 frequencies with a limited number of satellites in view. Full article

Continuous monitoring of natural human gait in real-life environments is essential in many applications including disease monitoring, rehabilitation, and professional sports. Wearable inertial measurement units are successfully used to measure body kinematics in real-life environments and to estimate total walking ground reaction forces $GRF\left(t\right)$ using equations of motion. However, for inverse dynamics and clinical gait analysis, the $GRF\left(t\right)$ of each foot is required separately. Using an experimental dataset of 1243 tri-axial separate-foot $GRF\left(t\right)$ time histories measured by the authors across eight years, this study proposes the ‘Twin Polynomial Method’ (TPM) to estimate the tri-axial left and right foot $GRF\left(t\right)$ signals from the total $GRF\left(t\right)$ signals. For each gait cycle, TPM fits polynomials of degree five, eight, and nine to the known single-support part of the left and right foot vertical, anterior-posterior, and medial-lateral $GRF\left(t\right)$ signals, respectively, to extrapolate the unknown double-support parts of the corresponding $GRF\left(t\right)$ signals. Validation of the proposed method both with force plate measurements (gold standard) in the laboratory, and in real-life environment showed a peak-to-peak normalized root mean square error of less than 2.5%, 6.5% and 7.5% for the estimated $GRF\left(t\right)$ signals in the vertical, anterior-posterior and medial-lateral directions, respectively. These values show considerable improvement compared with the currently available $GRF\left(t\right)$ decomposition methods in the literature. Full article

Human activity recognition (HAR) is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applied to HAR. Data segmentation using a sliding window is a basic step during the HAR procedure, wherein the window length directly affects recognition performance. However, the window length is generally randomly selected without systematic study. In this study, we examined the impact of window length on smartphone sensor-based human motion and pose pattern recognition. With data collected from smartphone sensors, we tested a range of window lengths on five popular machine-learning methods: decision tree, support vector machine, K-nearest neighbor, Gaussian naïve Bayesian, and adaptive boosting. From the results, we provide recommendations for choosing the appropriate window length. Results corroborate that the influence of window length on the recognition of motion modes is significant but largely limited to pose pattern recognition. For motion mode recognition, a window length between 2.5–3.5 s can provide an optimal tradeoff between recognition performance and speed. Adaptive boosting outperformed the other methods. For pose pattern recognition, 0.5 s was enough to obtain a satisfactory result. In addition, all of the tested methods performed well. Full article

The detection of multiple fluids using a single chip has been attracting attention recently. A TM₀₂ quarter-mode substrate-integrated waveguide resonator designed at 5.81 GHz on RT/duroid 6010LM with a return loss of 13 dB and an unloaded quality factor of Q ≈ 13 generates two distinct strong electric fields that can be manipulated to simultaneously detect two chemicals. Two asymmetric channels engraved in a polydimethylsiloxane sheet are loaded with analyte to produce a unique resonance frequency in each case, regardless of the dielectric constants of the liquids. Keeping in view the nature of lossy liquids such as ethanol, the initial structure and channels are optimized to ensure a reasonable return loss even in the case of loading lossy liquids. After loading the empty channels, Q is evaluated as 43. Ethanol (E) and deionized water (DI) are simultaneously loaded to demonstrate the detection of all possible combinations: [Air, Air], [E, DI], [DI, E], [E, E], and [DI, DI]. The proposed structure is miniaturized while exhibiting a performance comparable to that of existing multichannel microwave chemical sensors. Full article

This article presents a non-destructive methodology to determine the modulus of elasticity (MOE) in static bending of wood through the use of near-infrared (NIR) spectroscopy. Wood specimens were obtained from Quercus mongolica growing in Northeast of China. The NIR spectra of specimens were acquired by using a one-chip NIR fiber optic spectrometer whose spectral range was 900~1900 nm. The raw spectra of specimens were pretreated by multiplication scatter correlation and Savitzky-Golay smoothing and differentiation filter. To reduce the dimensions of data and complexity of modeling, the synergy interval partial least squares and successive projections algorithm were applied to extract the characteristic wavelengths, which had closing relevance with the MOE of wood, and five characteristic wavelengths were selected from full 117 variables of a spectrum. Taking the characteristic wavelengths as input values, partial least square regression (PLSR) and the propagation neural network (BPNN) were implemented to establish calibration models. The predictive ability of the models was estimated by the coefficient of determination (r_p) and the root mean square error of prediction (RMSEP) and in the prediction set. In comparison with the predicted results of the models, BPNN performed better results with the higher r_p of 0.91 and lower RMSEP of 0.76. The results indicate that it is feasible to accurately determine the MOE of wood by using the NIR spectroscopy technique. Full article

The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a joint energy supply and routing path selection algorithm to extend the network lifetime based on an initiative power supply. We develop a two-stage energy replenishment strategy to supplement the energy consumption of nodes as much as possible. Furthermore, the influence of charging factors on the selection of next-hop nodes in data routing is considered. The simulation results show that our algorithm effectively prolong the network lifetime, and different demands of network delay and energy consumption can be obtained by dynamically adjusting parameters. Full article

Pipes are one of the key elements in the construction of ships, which usually contain between 15,000 and 40,000 of them. This huge number, as well as the variety of processes that may be performed on a pipe, require rigorous identification, quality assessment and traceability. Traditionally, such tasks have been carried out by using manual procedures and following documentation on paper, which slows down the production processes and reduces the output of a pipe workshop. This article presents a system that allows for identifying and tracking the pipes of a ship through their construction cycle. For such a purpose, a fog computing architecture is proposed to extend cloud computing to the edge of the shipyard network. The system has been developed jointly by Navantia, one of the largest shipbuilders in the world, and the University of A Coruña (Spain), through a project that makes use of some of the latest Industry 4.0 technologies. Specifically, a Cyber-Physical System (CPS) is described, which uses active Radio Frequency Identification (RFID) tags to track pipes and detect relevant events. Furthermore, the CPS has been integrated and tested in conjunction with Siemens’ Manufacturing Execution System (MES) (Simatic IT). The experiments performed on the CPS show that, in the selected real-world scenarios, fog gateways respond faster than the tested cloud server, being such gateways are also able to process successfully more samples under high-load situations. In addition, under regular loads, fog gateways react between five and 481 times faster than the alternative cloud approach. Full article

In this paper, we investigate the state estimation of systems with unknown covariance non-Gaussian measurement noise. A novel improved Gaussian filter (GF) is proposed, where the maximum correntropy criterion (MCC) is used to suppress the pollution of non-Gaussian measurement noise and its covariance is online estimated through the variational Bayes (VB) approximation. MCC and VB are integrated through the fixed-point iteration to modify the estimated measurement noise covariance. As a general framework, the proposed algorithm is applicable to both linear and nonlinear systems with different rules being used to calculate the Gaussian integrals. Experimental results show that the proposed algorithm has better estimation accuracy than related robust and adaptive algorithms through a target tracking simulation example and the field test of an INS/DVL integrated navigation system. Full article

Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus, the accuracy of the state prediction has a significant influence on the final results of filtering. There exist unpredictable approximation errors in the process of filtering due to state propagation, discretization, linearization or other adverse effects. The idea of online covariance adaption is proposed in this work, where the post covariance information is proved to be effective for the covariance adaption. With theoretical deduction, the relationship between the posterior covariance and the priori covariance is investigated; the priori covariance is modified online based on the feedback rule of covariance updating. The general framework integrates the continuous-discrete cubature Kalman filtering and the feedback rule of covariance updating. Numerical results illustrated that the proposed method has advantages over decreasing unpredictable errors and improving the computational accuracy and efficiency. Full article

The detailed design considerations for the printed RFID-based sensor system is presented in this paper. Starting from material selection and metallization method, this paper discusses types of RFID-based sensors (single- & dual-tag sensor topologies), design procedures, and performance evaluation methods for the wireless sensor system. The electrical properties of the paper substrates (cellulose-based and synthetic papers) and the silver nano-particle-based conductive film are thoroughly characterized for RF applications up to 8 GHz. The reported technology could potentially set the foundation for truly “green”, low-cost, scalable wireless topologies for autonomous Internet-of-Things (IoT), bio-monitoring, and “smart skin” applications. Full article

The system architecture for an adaptive multiple input multiple output (MIMO) radar-communication transceiver is proposed. A waveform design approach for communication data embedding into MIMO radar pulse using M-ary position phase shift keying (MPPSK) waveforms is introduced. A waveform optimization algorithm for the adaptive system is presented. The algorithm aims to improve the target detection performance by maximizing the relative entropy (RE) between the distributions under existence and absence of the target, and minimizing the mutual information (MI) between the current received signals and the estimated signals in the next time instant. The proposed system adapts its MPPSK modulated inter-pulse duration to suit the time-varying environment. With subsequent iterations of the algorithm, simulation results show an improvement in target impulse response (TIR) estimation and target detection probability. Meanwhile, the system is able to transmit data of several Mbps with low symbol error rates. Full article

Fiber Bragg grating (FBG) is considered a good candidate for acoustic emission (AE) measurement. The sensing and measurement in traditional FBG-based AE systems are based on the variation in laser intensity induced by the Bragg wavelength shift. This paper presents a sensing system by combining self-mixing interference (SMI) in a laser diode and FBG for AE measurement, aiming to form a new compact and cost-effective sensing system. The measurement model of the overall system was derived. The performance of the presented system was investigated from both aspects of theory and experiment. The results show that the proposed system is able to measure AE events with high resolution and over a wide dynamic frequency range. Full article

Delamanintions and reinforcement corrosion are two common problems in concrete bridge decks. No single nondestructive testing method (NDT) is able to provide comprehensive characterization of these defects. In this work, two NDT methods, acoustic scanning and Ground Penetrating Radar (GPR), were used to image a straight concrete bridge deck and a curved intersection ramp bridge. An acoustic scanning system has been developed for rapid delamination mapping. The system consists of metal-ball excitation sources, air-coupled sensors, and a GPS positioning system. The acoustic scanning results are presented as a two-dimensional image that is based on the energy map in the frequency range of 0.5–5 kHz. The GPR scanning results are expressed as the GPR signal attenuation map to characterize concrete deterioration and reinforcement corrosion. Signal processing algorithms for both methods are discussed. Delamination maps from the acoustic scanning are compared with deterioration maps from the GPR scanning on both bridges. The results demonstrate that combining the acoustic and GPR scanning results will provide a complementary and comprehensive evaluation of concrete bridge decks. Full article

This paper is concerned to the fire localization problem for large-space buildings. Two kinds of circular fire source arrangement localization methods are proposed on the basis of the dynamic optimization technology. In the Range-Point-Range frame, a dynamic optimization localization is proposed to globally estimate the circle center of the circular arrangement to be determined based on all the point estimates of the fire source. In the Range-Range-Range frame, a dynamic optimization localization method is developed by solving a non-convex optimization problem. In this way, the circle center and the radius are obtained simultaneously. Additionally, the dynamic angle bisector method is evaluated. Finally, a simulation with three simulation scenes is provided to illustrate the effectiveness and availability of the proposed methods. Full article

This paper presents a gaseous oxygen detection system based on time-resolved phosphorimetry (time-domain), which is used to investigate O${}_2$ optical transducers. The primary sensing elements were formed by incorporating iridium(III) and palladium(II) meso-tetrakis(pentafluorophenyl)porphyrin complexes (IrTFPP-CO-Cl and PdTFPP) in polystyrene (PS) solid matrices. Probe excitation was obtained using a violet light-emitting diode (LED) (low power), and the resulting phosphorescence was detected by a high-sensitivity compact photomultiplier tube. The detection system performance and the preparation of the transducers are presented along with their optical properties, phosphorescence lifetimes, calibration curves and photostability. The developed lifetime measuring system showed a good signal-to-noise ratio, and reliable results were obtained from the optodes, even when exposed to moderate levels of O${}_2$. The new IrTFPP-CO-Cl membranes exhibited room temperature phosphorescence and moderate sensitivity: <${\tau }_0$>/<${\tau }_{21\%}$> ratio of ≈6. A typically high degree of dynamic phosphorescence quenching was observed for the traditional indicator PdTFPP: <${\tau }_0$>/<${\tau }_{21\%}$> ratio of ≈36. Pulsed-source time-resolved phosphorimetry combined with a high-sensitivity photodetector can offer potential advantages such as: (i) major dynamic range, (ii) extended temporal resolution ($\Delta$$\tau$/$\Delta$[O${}_2$]) and (iii) high operational stability. IrTFPP-CO-Cl immobilized in polystyrene is a promising alternative for O${}_2$ detection, offering adequate photostability and potentially mid-range sensitivity over Pt(II) and Pd(II) metalloporphyrins. Full article

Pulsed eddy current (PEC) technology is another important non-contact nondestructive testing technology for defect detection. However, the temperature drift of the exciting coil has a considerable influence on the precision of PEC testing. The objective of this study is to investigate the temperature drift effect and reduce its impact. The temperature drift effect is analyzed theoretically and experimentally. The temperature drift effect on the peak-to-peak values of the output signal is investigated, and a temperature compensation method is proposed to reduce the effect of temperature variation. The results show that temperature drift has a negative impact on PEC testing and the temperature compensation method can effectively reduce the effect of temperature drift. Full article

Environmental sensors are exploited in smart homes for many purposes. Sensor data inherently carries behavioral information, possibly useful to infer wellness and health-related insights in an indirect fashion. In order to exploit such features, however, powerful analytics are needed to convert raw sensor output into meaningful and accessible knowledge. In this paper, a complete monitoring architecture is presented, including home sensors and cloud-based back-end services. Unsupervised techniques for behavioral data analysis are presented, including: (i) regression and outlier detection models (also used as feature extractors for more complex models); (ii) statistical hypothesis testing frameworks for detecting changes in sensor-detected activities; and (iii) a clustering process, leveraging deep learning techniques, for extracting complex, multivariate patterns from daily sensor data. Such methods are discussed and evaluated on real-life data, collected within several EU-funded projects. Overall, the presented methods may prove very useful to build effective monitoring services, suitable for practical exploitation in caregiving activities, complementing conventional telemedicine techniques. Full article

With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other places. Since the power supplies of many mobile sensor nodes are batteries, green communication is an effective approach of reducing the energy consumption of a network and extending its longevity. To reduce the energy consumption of networks, all factors that negatively influence the lifetime should be considered. The degree constraint minimum spanning tree (DCMST) is introduced in this study to consider all the heterogeneous factors and assign weights for the next step of the evaluation. Then, a genetic algorithm (GA) is introduced to cluster sensor nodes in the network and balance energy consumption according to several heterogeneous factors and routing paths from DCMST. Based on a comparison of the simulation results, the optimization routing algorithm proposed in this study for use in green communication in underground mines can effectively reduce the network energy consumption and extend the lifetimes of networks. Full article

A glucose biosensor was utilized as a platform for the time-temperature integrator (TTI), a device for intelligent food packaging. The TTI system is composed of glucose oxidase, glucose, a pH indicator, and a three-electrode potentiostat, which produces an electrical signal as well as color development. The reaction kinetics of these response variables were analyzed under isothermal conditions. The reaction rates of the electrical current and color changes were 0.0360 ± 0.0020 (95% confidence limit), 0.0566 ± 0.0026, 0.0716 ± 0.0024, 0.1073 ± 0.0028 µA/min, and 0.0187 ± 0.0005, 0.0293 ± 0.0018, 0.0363 ± 0.0012, 0.0540 ± 0.0019 1/min, at 5, 15, 25, and 35 °C, respectively. The Arrhenius activation energy of the current reaction (Ea_current) was 25.0 ± 1.6 kJ/mol and the Ea_color of the color reactions was 24.2 ± 0.6 kJ/mol. The similarity of these Ea shows agreement in the prediction of food qualities between the electrical signal and color development. Consequently, the function of the new time-temperature integrator system could be extended to that of a biosensor compatible with any electrical utilization equipment. Full article