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In the past three decades, remote sensing-based models for estimating crop yield have addressed critical problems of general food security, as the unavailability of grains such as rice creates serious worldwide food insecurity problems. The main purpose of this study was to compare the potential of time-series Landsat-8 and Sentinel-2 data to predict rice yield several weeks before harvest on a regional scale.

To this end, the sum of normalized difference vegetation index (NDVI)-based models created the best agreement with actual yield data at the golden time window of six weeks before harvest when rice grains were in milky and mature growth stages. The application of nine other vegetation indicators was also investigated in the golden time window in comparison to NDVI.

The findings of this study demonstrate the viability of identifying locations with poor and superior performance in terms of production management approaches through a rapid and economical solution for early rice grain yield assessment. Results indicated that while some of those, such as enhanced vegetation index (EVI) and optimized soil adjusted vegetation index, were able to estimate rice yield with high accuracy, NDVI is still the best indicator to predict rice yield before harvest. However, experiments can be conducted in different regions in future studies to evaluate the generalizability of the approach.

To achieve this objective, the authors considered the following purposes: using Sentinel-2 time-series data, determining the appropriate growth stage for estimating rice yield and evaluating different vegetation indices for estimating rice yield.

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects.

Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted.

In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested.

Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

Detecting O₂ gas in a confined space at room temperature is particularly important to monitor the work process of precision equipment. This study aims to propose a miniaturized, low-cost, mass-scale produced O₂ sensor operating around 30°C.

The O₂ sensor based on lanthanum fluoride (LaF₃) solid electrolyte thin film was developed using MEMS technology. The principle of the sensor was a galvanic cell H₂O, O₂, Pt | LaF₃ | Sn, SnF₂ |, in which the Sn film was prepared by magnetron sputtering, and the LaF₃ film was prepared by thermal resistance evaporation.

Through pretreatments, the sensor’s response signal to 40% oxygen concentration was enhanced from 1.9 mV to 46.0 mV at 30°C and 97.0% RH. Tests at temperatures from 30°C to 50°C and humidity from 32.4% RH to 97.0% RH indicated that the output electromotive force (EMF) has a linear relationship with the logarithm of the oxygen concentration. The sensitivity of the sensor increases with an increase in both humidity and temperature in the couple mode, and the EMF of the sensor follows well with the Nernst equation at different temperatures and humidity.

This research could be applied to monitor the oxygen concentration below 25% in confined spaces at room temperature safely without a power supply.

The relationship between temperature and humidity coupling and the response of the sensor was obtained. The nano-film material was integrated with the MEMS process. It is expected to be practically applied in the future.

This paper aims to study the influence of different reinforcement methods on crack monitoring characteristics of eddy current array sensors, and the sensors with two different reinforcement methods, SUS304 reinforcement and permalloy reinforcement, are proposed.

First, the finite element model of the sensor is established to analyze the influence of the reinforcement plate’s electromagnetic parameters on the crack identification sensitivity. Then, the crack monitoring accuracy test of sensors with two reinforcement methods is carried out. Finally, the fatigue crack monitoring experiments with bolt tightening torques of 45 and 63 N · m are carried out, respectively.

In this study, it is found that the crack identification sensitivity of the sensor can be improved by increasing the relative permeability of the reinforcement plate. The crack monitoring accuracy of the sensors with two different reinforcement methods is about 1 mm. And the crack identification sensitivity of the sensor reinforced by permalloy reinforcement plate is significantly higher than that of the sensor reinforced by SUS304 reinforcement plate.

The sensor reinforced by reinforcement plate can work normally under the squeezing action of the bolt, and the crack monitoring sensitivity of the sensor can be significantly improved by using the reinforcement plate with high relative permeability.

The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be skin-tight and less exposed, reducing production processes and increasing productivity. Study its electrical conductivity in different yarn materials, knit processes and deformation ranges. The analysis is compared to provide some basis for the design of the electrodes.

The method includes five operations: (1) Analysis of the morphological appearance, tensile variation, fiber material properties and electrical conductivity of high-elastic and filament silver-plated conductive yarns. (2) Based on the knitting process of the floating yarn structure, three-dimensional modeling of the flexible sensor was carried out to explore the influence of knitting process changes on appearance characteristics. (3) The fabric samples are knitted by different silver-plated conductive yarns with different structures. Processing of experimental samples to finished size by advance shrinkage. (4) Measure the resistance of the experimental sample after the machine has been lowered and after pre-shrinking. Use the stretching machine to simulate a wearing experiment and measure the change in resistance of the sample in the 0–15% stretching range. (5) Analyze the influence factors on the conductive performance of the flexible sensor to determine whether it is suitable for textile flexible sensors.

For the float knitted flexible sensors, the floating wire projection is influenced by the elasticity of the fabric and the length of the floating wire. Compared to the plain knitted flexible sensors, it has less resistance variation and better electrical properties, making it suitable for making electrodes for textile structures. In addition, the knitting method is integrated with the intelligent monitoring clothing, which saves the process for the integration of the flexible sensor, realizes positioning and fixed-point knitting.

The sensor technology of the designed weft-knitted float structure is varied and can be freely combined and designed in a wide range. Within the good electrical conductivity, the flexible sensor can realize integrated knitting, positioning monitoring, integrating into the appearance of clothing. It can also focus on the wearing experience of wearable products so that the appearance of the monitoring clothing is close to the clothes we wear in our daily life.

In this paper, an integrated positioning knitting flexible sensor based on the weft knitting float structure is studied. The improved knitting process allows the sensing contact surface to be close to the skin and reduces the integration process. The relationship between the exposure of the silver-plated yarn on the clothing surface and the electrical conductivity is analyzed. Within a certain conductive performance, reduces the exposed area of the conductive yarn on the clothing surface and proposes a design reference for the flexible sensor appearance.