ALBERT

Description: This paper reports on a two-step approach for optimally determining the location and severity of damage in beam structures under flexural vibration. The first step focuses on damage location detection. This is done by defining the damage index called relative wavelet packet entropy (RWPE). The damage severities of the model in terms of loss of stiffness are assessed in the second step using the inverse solution of equations of motion of a structural system in the wavelet domain. For this purpose, the connection coefficient of the scaling function to convert the equations of motion in the time domain into the wavelet domain is applied. Subsequently, the dominant components based on the relative energies of the wavelet packet transform (WPT) components of the acceleration responses are defined. To obtain the best estimation of the stiffness parameters of the model, the least squares error minimization is used iteratively over the dominant components. Then, the severity of the damage is evaluated by comparing the stiffness parameters of the identified model before and after the occurrence of damage. The numerical and experimental results demonstrate that the proposed method is robust and effective for the determination of damage location and accurate estimation of the loss in stiffness due to damage.

Description: In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

Description: In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach.

Description: Ensemble classifiers are being widely used for the classification of spectroscopic data. In this regard, the random forest (RF) ensemble has been successfully applied in an array of applications, and has proven to be robust in handling high dimensional data. More recently, several variants of the traditional RF algorithm including rotation forest (rotF) and oblique random forest (oRF) have been applied to classifying high dimensional data. In this study we compare the traditional RF, rotF, and oRF (using three different splitting rules, i.e., ridge regression, partial least squares, and support vector machine) for the classification of healthy and infected Pinus radiata seedlings using high dimensional spectroscopic data. We further test the robustness of these five ensemble classifiers to reduced spectral resolution by spectral resampling (binning) of the original spectral bands. The results showed that the three oblique random forest ensembles outperformed both the traditional RF and rotF ensembles. Additionally, the rotF ensemble proved to be the least robust of the five ensembles tested. Spectral resampling of the original bands provided mixed results. Nevertheless, the results demonstrate that using spectral resampled bands is a promising approach to classifying asymptomatic stress in Pinus radiata seedlings.

Description: Energies, Vol. 10, Pages 1022: Opportunities and Challenges for Near-Field Wireless Power Transfer: A Review Energies doi: 10.3390/en10071022 Authors: Aqeel Mahmood Jawad Rosdiadee Nordin Sadik Kamel Gharghan Haider Mahmood Jawad Mahamod Ismail Traditional power supply cords have become less important because they prevent large-scale utilization and mobility. In addition, the use of batteries as a substitute for power cords is not an optimal solution because batteries have a short lifetime, thereby increasing the cost, weight, and ecological footprint of the hardware implementation. Their recharging or replacement is impractical and incurs operational costs. Recent progress has allowed electromagnetic wave energy to be transferred from power sources (i.e., transmitters) to destinations (i.e., receivers) wirelessly, the so-called wireless power transfer (WPT) technique. New developments in WPT technique motivate new avenues of research in different applications. Recently, WPT has been used in mobile phones, electric vehicles, medical implants, wireless sensor network, unmanned aerial vehicles, and so on. This review highlights up-to-date studies that are specific to near-field WPT, which include the classification, comparison, and potential applications of these techniques in the real world. In addition, limitations and challenges of these techniques are highlighted at the end of the article.

Description: Sensors, Vol. 17, Pages 1781: Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review Sensors doi: 10.3390/s17081781 Authors: Haider Jawad Rosdiadee Nordin Sadik Gharghan Aqeel Jawad Mahamod Ismail Wireless sensor networks (WSNs) can be used in agriculture to provide farmers with a large amount of information. Precision agriculture (PA) is a management strategy that employs information technology to improve quality and production. Utilizing wireless sensor technologies and management tools can lead to a highly effective, green agriculture. Based on PA management, the same routine to a crop regardless of site environments can be avoided. From several perspectives, field management can improve PA, including the provision of adequate nutrients for crops and the wastage of pesticides for the effective control of weeds, pests, and diseases. This review outlines the recent applications of WSNs in agriculture research as well as classifies and compares various wireless communication protocols, the taxonomy of energy-efficient and energy harvesting techniques for WSNs that can be used in agricultural monitoring systems, and comparison between early research works on agriculture-based WSNs. The challenges and limitations of WSNs in the agricultural domain are explored, and several power reduction and agricultural management techniques for long-term monitoring are highlighted. These approaches may also increase the number of opportunities for processing Internet of Things (IoT) data.

Description: Energies, Vol. 10, Pages 1693: The Amalgamation of SVR and ANFIS Models with Synchronized Phasor Measurements for On-Line Voltage Stability Assessment Energies doi: 10.3390/en10111693 Authors: Mohammed Amroune Ismail Musirin Tarek Bouktir Muhammad Othman This paper presents the application of support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS) models that are amalgamated with synchronized phasor measurements for on-line voltage stability assessment. As the performance of SVR model extremely depends on the good selection of its parameters, the recently developed ant lion optimizer (ALO) is adapted to seek for the SVR’s optimal parameters. In particular, the input vector of ALO-SVR and ANFIS soft computing models is provided in the form of voltage magnitudes provided by the phasor measurement units (PMUs). In order to investigate the effectiveness of ALO-SVR and ANFIS models towards performing the on-line voltage stability assessment, in-depth analyses on the results have been carried out on the IEEE 30-bus and IEEE 118-bus test systems considering different topologies and operating conditions. Two statistical performance criteria of root mean square error (RMSE) and correlation coefficient (R) were considered as metrics to further assess both of the modeling performances in contrast with the power flow equations. The results have demonstrated that the ALO-SVR model is able to predict the voltage stability margin with greater accuracy compared to the ANFIS model.

Description: Sensors, Vol. 18, Pages 2175: UV-Vis Spectroscopy: A New Approach for Assessing the Color Index of Transformer Insulating Oil Sensors doi: 10.3390/s18072175 Authors: Yang Sing Leong Pin Jern Ker M. Z. Jamaludin Saifuddin M. Nomanbhay Aiman Ismail Fairuz Abdullah Hui Mun Looe Chin Kim Lo Monitoring the condition of transformer oil is considered to be one of the preventive maintenance measures and it is very critical in ensuring the safety as well as optimal performance of the equipment. Various oil properties and contents in oil can be monitored such as acidity, furanic compounds and color. The current method is used to determine the color index (CI) of transformer oil produces an error of 0.5 in measurement, has high risk of human handling error, additional expense such as sampling and transportations, and limited samples can be measured per day due to safety and health reasons. Therefore, this work proposes the determination of CI of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. Results show a good correlation between the CI of transformer oil and the absorbance spectral responses of oils from 300 nm to 700 nm. Modeled equations were developed to relate the CI of the oil with the cutoff wavelength and absorbance, and with the area under the curve from 360 nm to 600 nm. These equations were verified with another set of oil samples. The equation that describes the relationship between cutoff wavelength, absorbance and CI of the oil shows higher accuracy with root mean square error (RMSE) of 0.1961.

Description: Sensors, Vol. 18, Pages 2184: Internet-Of-Things in Motion: A UAV Coalition Model for Remote Sensing in Smart Cities Sensors doi: 10.3390/s18072184 Authors: Adiel Ismail Bigomokero Antoine Bagula Emmanuel Tuyishimire Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently than if done by humans. These include remote sensing tasks where drones can be required to form coalitions by pooling their resources to meet the service requirements at different locations of interest in a city. During such coalition formation, finding the shortest path from a source to a location of interest is key to efficient service delivery. For fixed-wing UAVs, Dubins curves can be applied to find the shortest flight path. When a UAV flies to a location of interest, the angle or orientation of the UAV upon its arrival is often not important. In such a case, a simplified version of the Dubins curve consisting of two instead of three parts can be used. This paper proposes a novel model for UAV coalition and an algorithm derived from basic geometry that generates a path derived from the original Dubins curve for application in remote sensing missions of fixed-wing UAVs. The algorithm is tested by incorporating it into three cooperative coalition formation algorithms. The performance of the model is evaluated by varying the number of types of resources and the sensor ranges of the UAVs to reveal the relevance and practicality of the proposed model.

Description: Energies, Vol. 11, Pages 1969: Single-Tube and Multi-Turn Coil Near-Field Wireless Power Transfer for Low-Power Home Appliances Energies doi: 10.3390/en11081969 Authors: Aqeel Mahmood Jawad Rosdiadee Nordin Sadik Kamel Gharghan Haider Mahmood Jawad Mahamod Ismail Mahmood Jawad Abu-AlShaeer Single-tube loop coil (STLC) and multi-turn copper wire coil (MTCWC) wireless power transfer (WPT) methods are proposed in this study to overcome the challenges of battery life during low-power home appliance operations. Transfer power, efficiency, and distance are investigated for charging mobile devices on the basis of the two proposed systems. The transfer distances of 1–15 cm are considered because the practicality of this range has been proven to be reliable in the current work on mobile device battery charging. For STLC, the Li-ion battery is charged with total system efficiencies of 86.45%, 77.08%, and 52.08%, without a load, at distances of 2, 6, and 15 cm, respectively. When the system is loaded with 100 Ω at the corresponding distances, the transfer efficiencies are reduced to 80.66%, 66.66%, and 47.04%. For MTCWC, the battery is charged with total system efficiencies of 88.54%, 75%, and 52.08%, without a load, at the same distances of 2, 6, and 15 cm. When the system is loaded with 100 Ω at the corresponding distances, the transfer efficiencies are drastically reduced to 39.52%, 33.6%, and 15.13%. The contrasting results, between the STLC and MTCWC methods, are produced because of the misalignment between their transmitters and receiver coils. In addition, the diameter of the MTCWC is smaller than that of the STLC. The output power of the proposed system can charge the latest smartphone in the market, with generated output powers of 5 W (STLC) and 2 W (MTCWC). The above WPT methods are compared with other WPT methods in the literature.