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A mechanical trigger inertial micro-switch with spring stationary electrode is proposed and fabricated by surface micromachining. The elastic contact process and stability performance are evaluated through experimental tests performed using a drop hammer. The test results show that the contact time is about 110 μs and 100 μs when the threshold acceleration is 480 g and the overload acceleration is 602 g, respectively. The vibration process of the electrodes is explained through an established physical mode. The elastic contact process is analyzed and discussed by Finite Element Analysis (FEA) simulations, which indicated that the contact time is about 65 μs when the threshold acceleration is 600 g. At the same time, this result also proved that the contact time could be extended effectively by the designed spring stationary electrode. The overload acceleration (800 g) has been applied to the Finite-Element model in ANSYS, the contact process indicated that the proof mass contacted with stationary electrode three times, and there was no bounce phenomenon during contact process, which fully proved that the stable contact process can be realized at high acceleration owing to the designed elastic stationary electrode. [ABSTRACT FROM AUTHOR]

Radiator reliability is crucial in environments characterized by high temperatures and friction, where prompt interventions are often required to prevent system failures. This study introduces a proactive approach to radiator fault diagnosis, leveraging the integration of the Gaussian Mixture Model and Long-Short Term Memory autoencoders. Vibration signals from radiators were systematically collected through randomized durability vibration bench tests, resulting in four operating states—two normal, one unknown, and one faulty. Time-domain statistical features of these signals were extracted and subjected to Principal Component Analysis to facilitate efficient data interpretation. Subsequently, this study discusses the comparative effectiveness of the Gaussian Mixture Model and Long Short-Term Memory in fault detection. Gaussian Mixture Models are deployed for initial fault classification, leveraging their clustering capabilities, while Long-Short Term Memory autoencoders excel in capturing time-dependent sequences, facilitating advanced anomaly detection for previously unencountered faults. This alignment offers a potent and adaptable solution for radiator fault diagnosis, particularly in challenging high-temperature or high-friction environments. Consequently, the proposed methodology not only provides a robust framework for early-stage fault diagnosis but also effectively balances diagnostic capabilities during operation. Additionally, this study presents the foundation for advancing reliability life assessment in accelerated life testing, achieved through dynamic threshold adjustments using both the absolute log-likelihood distribution of the Gaussian Mixture Model and the reconstruction error distribution of the Long-Short Term Memory autoencoder model. [ABSTRACT FROM AUTHOR]

Objective gait analysis provides valuable information about the locomotion characteristics of sound and lame horses. Due to their high accuracy and sensitivity, inertial measurement units (IMUs) have gained popularity over objective measurement techniques such as force plates and optical motion capture (OMC) systems. IMUs are wearable sensors that measure acceleration forces and angular velocities, providing the possibility of a non-invasive and continuous monitoring of horse gait during walk, trot, or canter during field conditions. The present narrative review aimed to describe the inertial sensor technologies and summarize their role in equine gait analysis. The literature was searched using general terms related to inertial sensors and their applicability, gait analysis methods, and lameness evaluation. The efficacy and performance of IMU-based methods for the assessment of normal gait, detection of lameness, analysis of horse–rider interaction, as well as the influence of sedative drugs, are discussed and compared with force plate and OMC techniques. The collected evidence indicated that IMU-based sensor systems can monitor and quantify horse locomotion with high accuracy and precision, having comparable or superior performance to objective measurement techniques. IMUs are reliable tools for the evaluation of horse–rider interactions. The observed efficacy and performance of IMU systems in equine gait analysis warrant further research in this population, with special focus on the potential implementation of novel techniques described and validated in humans. [ABSTRACT FROM AUTHOR]

Silicon-based kinetic energy converters employing variable capacitors, also known as electrostatic vibration energy harvesters, hold promise as power sources for Internet of Things devices. However, for most wireless applications, such as wearable technology or environmental and structural monitoring, the ambient vibration is often at relatively low frequencies (1–100 Hz). Since the power output of electrostatic harvesters is positively correlated to the frequency of capacitance oscillation, typical electrostatic energy harvesters, designed to match the natural frequency of ambient vibrations, do not produce sufficient power output. Moreover, energy conversion is limited to a narrow range of input frequencies. To address these shortcomings, an impacted-based electrostatic energy harvester is explored experimentally. The impact refers to electrode collision and it triggers frequency upconversion, namely a secondary high-frequency free oscillation of the electrodes overlapping with primary device oscillation tuned to input vibration frequency. The main purpose of high-frequency oscillation is to enable additional energy conversion cycles since this will increase the energy output. The devices investigated were fabricated using a commercial microfabrication foundry process and were experimentally studied. These devices exhibit non-uniform cross-section electrodes and a springless mass. The non-uniform width electrodes were used to prevent pull-in following electrode collision. Springless masses from different materials and sizes, such as 0.5 mm diameter Tungsten carbide, 0.8 mm diameter Tungsten carbide, zirconium dioxide, and silicon nitride, were added in an attempt to force collisions over a range of applied frequencies that would not otherwise result in collisions. The results show that the system operates over a relatively wide frequency range (up to 700 Hz frequency range), with the lower limit far below the natural frequency of the device. The addition of the springless mass successfully increased the device bandwidth. For example, at a low peak-to-peak vibration acceleration of 0.5 g (peak-to-peak), the addition of a zirconium dioxide ball doubled the device's bandwidth. Testing with different balls indicates that the different sizes and material properties have different effects on the device's performance, altering its mechanical and electrical damping. [ABSTRACT FROM AUTHOR]

Fiber-reinforced polymer composites are an excellent choice for bridge decks due to high strength, lightweight, resistance to corrosion, and long-term durability with a 100-year design life. Structural health monitoring is useful for the long-term assessment of the condition of the bridge structure and obtaining a response to complex loads considering environmental conditions. Bridge structures have been studied primarily using distributed fiber optic sensing, such as Brillouin scattering; however, critical events, including damage detection, can be missed due to low spatial resolution. There is also a critical need to conduct a comprehensive study of static and dynamic loading simultaneously for fiber-reinforced composite bridge structures. In this study, a novel approach was implemented using two sensor technologies, optical frequency domain reflectometry and fiber Bragg grating-based sensors, embedded in a glass-fiber-reinforced composite bridge deck to simultaneously monitor the deformation response of the bridge structure. The optical frequency domain reflectometry sensor utilizing Rayleigh scattering provides high spatial strain resolution were positioned strategically based on expected stress distributions to measure strain in the longitudinal, transverse, and diagonal directions along the span of the composite bridge. Furthermore, fiber Bragg grating based sensors are used to monitor the response to dynamic vehicular loading and deformations from an automotive-crash-type event on the bridge structure. To monitor environmental variables such as temperature, a custom wireless configured sensor package was developed for the study and integrated with a composite bridge located in Morgan County, Tennessee. Additionally, a triaxial accelerometer was used to monitor the vehicular dynamic loading of the composite bridge deck in parallel with fiber Bragg grating sensors. When appropriate, mid-point displacements were compared with strain-distribution measurements from the fiber optic sensor-based data. [ABSTRACT FROM AUTHOR]

Due to the mechanical nature of container handling operations, as well as natural factors, container and handling infrastructure suffers various types of damage during use, especially within the tight and enclosed environments of a ship's hull. In this operational environment, it is critical to detect any sort of physical impacts between the vertical cell guides of the ship's hull and the container. Currently, an inspection of impacts and evaluation of any consequences is performed manually, via visual inspection processes. This process is time-consuming and relies on the technical expertise of the personnel involved. In this paper, we propose a five-step impact-detection methodology (IDM), intended to detect only the most significant impact events based on acceleration data. We conducted real measurements in a container terminal using a sensory device placed on the spreader of the quay crane. The proposed solution identified an average of 12.8 container impacts with the vertical cell guides during common handling operations. In addition, the results indicate that the presented IDM can be used to recognize repeated impacts in the same space of each bay of the ship, and can be used as a decision support tool for predictive maintenance systems. [ABSTRACT FROM AUTHOR]

Independent living of elderly persons in their homes requires support that can be provided with modern assistive technologies. Monitoring of elderly persons behaviour delivers valuable information that can be used for diagnosis and detection of health problems as well as triggering alerts in emergency situations. The paper includes a description of the ultra wideband system developed within Networked InfrasTructure for Innovative home Care Solutions (NITICS) Active and Assisted Living (AAL) project. The system can be used as a component of AAL platforms. It delivers data on users localization and has a fall detector functionality. The system also provides access to raw measurement results from Microelectromechanical Systems (MEMS) sensors embedded in the device worn by the monitored person. These data can be used in solutions intended for elderly person’s behaviour investigation. The system was investigated under laboratory conditions as well as in home environment. The detailed system description and results of performed tests are included in the article. [ABSTRACT FROM AUTHOR]

A novel micro-electro-mechanical systems (MEMS) inertial microswitch with a flexible contact-enhanced structure to extend the contact duration has been proposed in the present work. In order to investigate the stiffness k of the stationary electrodes, the stationary electrodes with different shapes, thickness h, width b, and length l were designed, analyzed, and simulated using ANSYS software. Both the analytical and the simulated results indicate that the stiffness k increases with thickness h and width b, while decreasing with an increase of length l, and it is related to the shape. The inertial micro-switches with different kinds of stationary electrodes were simulated using ANSYS software and fabricated using surface micromachining technology. The dynamic simulation indicates that the contact time will decrease with the increase of thickness h and width b, but increase with the length l, and it is related to the shape. As a result, the contact time decreases with the stiffness k of the stationary electrode. Furthermore, the simulated results reveal that the stiffness k changes more rapidly with h and l compared to b. However, overlarge dimension of the whole microswitch is contradicted with small footprint area expectation in the structure design. Therefore, it is unreasonable to extend the contact duration by increasing the length l excessively. Thus, the best and most convenient way to prolong the contact time is to reduce the thickness h of the stationary electrode while keeping the plane geometric structure of the inertial micro-switch unchanged. Finally, the fabricated micro-switches with different shapes of stationary electrodes have been evaluated by a standard dropping hammer system. The test maximum contact time under 288 g acceleration can reach 125 µs. It is shown that the test results are in accordance with the simulated results. The conclusions obtained in this work can provide guidance for the future design and fabrication of inertial microswitches. [ABSTRACT FROM AUTHOR]

Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics. However, traditional methods are not suited for robotic sensors, because of their low efficiency, instability, and non-smooth-generated paths. This paper adopts an optimizing function to generate several intermediate points and regress these discrete points to a quintic polynomial which can output a smooth trajectory for the robotic sensor. Simulations demonstrate that our approach is robust and efficient, and can be well applied in the CPSS field. [ABSTRACT FROM AUTHOR]

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudoWigner-Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. [ABSTRACT FROM AUTHOR]

Concussion is an inherent risk of participating in contact, combat, or collision sports, within which head impacts are numerous. Kinematic parameters such as peak linear and rotational acceleration represent primary measures of concussive head impacts. The ability to accurately measure and categorise such impact parameters in real time is important in health and sports performance contexts. The purpose of this study was to assess the accuracy of the latest HitIQ Nexus A9 instrumented mouthguard (HitIQ Pty. Ltd. Melbourne Australia) against reference sensors in an aluminium headform. The headform underwent drop testing at various impact intensities across the NOCSAE-defined impact locations, comparing the peak linear and rotational acceleration (PLA and PRA) as well as the shapes of the acceleration time-series traces for each impact. Mouthguard PLA and PRA measurements strongly correlated with (R2 = 0.996 and 0.994 respectively), and strongly agreed with (LCCC = 0.997) the reference sensors. The root mean square error between the measurement devices was 1 ± 0.6g for linear acceleration and 47.4 ± 35 rad/s2 for rotational acceleration. A Bland–Altman analysis found a systematic bias of 1% for PRA, with no significant bias for PLA. The instrumented mouthguard displayed high accuracy when measuring head impact kinematics in a laboratory setting. [ABSTRACT FROM AUTHOR]

Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN applications. In this study, we present a fully distributed solution, where leaks are detected in a water distribution network via only local collaborations between a sensor node and its close neighbors, without the need for long-distance transmissions via several hops to a centralized fusion center. A complete approach that includes the design, simulation, and physical measurements, showing how distributed computing implemented via a distributed Kalman filter improves the accuracy of leak detection and the power consumption is presented. The results from the physical implementation show that distributed data fusion increases the accuracy of leak detection while preserving WSN lifetime. [ABSTRACT FROM AUTHOR]

Advancements in protocols, computing paradigms, and electronics have enabled the development of wireless sensor networks (WSNs) with high potential for various location-based applications in different fields. One of the most important topics in WSNs is the localization in environments with sensor nodes being scattered randomly over a region. Localization techniques are often challenged by localization latency, efficient energy consumption, accuracy, environmental factors, and others. The objective of this study was to improve the technique for detecting the nearest Bluetooth Low Energy sensor, which would enable the development of more efficient mobile applications for location advertising at fairs, exhibitions, and museums. The technique proposed in this study was based on the iBeacon protocol, and it was tested in a controlled room with three environmental settings regarding the density of obstacles, as well as in a real-world setting at the Expo Museum at Postojna in Slovenia. The results of several independent measures, conducted in the controlled room and in the real-world environment, showed that the proposed algorithm outperformed the standard algorithm, especially in the environments with a medium or high densities of obstacles. The results of this study can be used for the more effective planning of placing beacons in space and for optimizing the algorithms for detecting transmitters in mobile location-based applications that provide users with contextual information based on their current location. [ABSTRACT FROM AUTHOR]

There is interest in using wearable sensors to measure infant movement patterns and physical activity, however, this approach is confounded by caregiver motion. The purpose of this study is to estimate the extent that caregiver motion confounds wearable sensor data in full-day studies of infant leg movements. We used wearable sensors to measure leg movements of a four-month-old infant across 8.5 hours, during which the infant was handled by the caregiver in a typical manner. A researcher mimicked the actions of the caregiver with a doll. We calculated 7744 left and 7107 right leg movements for the infant and 1013 left and 1115 right "leg movements" for the doll. In this case, approximately 15% of infant leg movements can be attributed to background motion of the caregiver. This case report is the first step toward removing caregiver-produced background motion from the infant wearable sensor signal. We have estimated the size of the effect and described the activities that were related to noise in the signal. Future research can characterize the noise in detail and systematically explore different methods to remove it. [ABSTRACT FROM AUTHOR]