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This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

Gas transmission pipelines are at constant risk of gas leakage or fire due to various atmospheric environments, corrosion on pipe metal surfaces and other external factors. This study aims to reduce the human and financial risks associated with gas transmission by regularly monitoring pipeline performance, controlling situations and preventing disasters.

Facility managers can monitor the status of gas transmission lines in real-time by integrating sensor information into a building information modeling (BIM) 3D model. Using the Monitoring Panel plugin, coded in C# programming language and operated through Navisworks software, the model provides up-to-date information on pipeline safety and performance.

By collecting project information on the BIM and installing critical sensors, this approach allows facility manager to observe the real-time safety status of gas pipelines. If any risks of gas leakage or accidents are identified by the sensors, the BIM model quickly shows the location of the incident, enabling facility managers to make the best decisions to reduce financial and life risks. This intelligent gas transmission pipeline approach changes traditional risk management and inspection methods, minimizing the risk of explosion and gas leakage in the environment.

This research distinguishes itself from related work by integrating sensor data into a BIM model for real-time monitoring and providing facility managers with up-to-date safety information. By leveraging intelligent gas transmission pipelines, the system enables quick identification and location of potential hazards, reducing financial and human risks associated with gas transmission.

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.

Tactile sensation is an important sensory function for robots in contact with the external environment. To better acquire tactile information about objects, this paper aims to propose a three-layer structure of the interdigital flexible tactile sensor.

The sensor consists of a bottom electrode layer, a middle pressure-sensitive layer and a top indenter layer. First, the pressure sensitive material, structure design, fabrication process and circuit design of the sensor are introduced. Then, the calibration and performance test of the designed sensor is carried out. Four functions are used to fit and calibrate the relationship between the output voltage of the sensor and the contact force. Finally, the contact force sensing test of different weight objects and the flexible test of the sensor are carried out.

The performance test results show that the sensitivity of the sensor is 0.93 V/N when it is loaded with 0–3 N and 0.23 V/N when it is loaded with 3–5 N. It shows good repeatability, and the cross-interference between the sensing units is generally low. The contact force sensing test results of different weight objects show that the proposed sensor performs well in contact force. Each part of the sensor is a flexible material, allowing the sensor to achieve bending deformation, so that the sensor can better perceive the contact signs of the grasped object.

The sensor can paste the surface of the paper robot’s gripper to measure the contact force of the grasping object and estimate the contour of the object.

In this paper, a three-layer interdigital flexible tactile sensor is proposed, and the structural parameters of the interdigital electrode are designed to improve the sensitivity and response speed of the sensor. The indenter with three shapes of the prism, square cylinder and hemisphere is preliminarily designed and the prism indenter with better conduction force is selected through finite element analysis, which can concentrate the external force in the sensing area to improve the sensitivity. The sensor designed in this paper can realize the measurement of contact force, which provides a certain reference for the field of robot tactile.

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.

The purpose of this study is to clarify the mechanism of ambient and transient temperature effects on piezoelectric pressure sensors, and to propose corresponding compensation measures. The temperature of the explosion field has a significant influence on the piezoelectric sensor used to measure the shock wave pressure. For accurate shock wave pressure measurement, based on the actual piezoelectric pressure sensors used in the explosion field, the effects of ambient and transient temperatures on the sensor should be studied.

The compensation method of the ambient temperature is discussed according to the sensor size and material. The theoretical analysis method of the transient temperature is proposed. For the transient temperature conduction problem of the sensor, the finite element simulation method of structure-temperature coupling is used to solve the temperature distribution of the sensor and the change in the contact force on the quartz crystal surface under the step and triangle temperatures. The simulation results are highly consistent with the theory.

Based on the analysis results, a transient temperature control method is proposed, in which 0.5 mm thick lubricating silicone grease is applied to the sensor diaphragm, and 0.2 mm thick fiberglass cloth is wrapped around the sensor side. Simulation experiments are carried out to verify the feasibility of the control method, and the results show that the control method effectively suppresses the output of the thermal parasitic.

The above thermal protection methods can effectively improve the measurement accuracy of shock wave pressure and provide technical support for the evaluation of the power of explosion damage.

This paper aims to design a magnetostrictive tactile sensor for surface depth detection. Unlike the human finger, although most tactile sensors have high sensitivity to pressure, they cannot detect millimeter-level depth information on the surface of objects precisely. To enhance the ability to detect surface depth information, a piezomagnetic sensor combining inverse magnetostrictive effect and bionic structure is developed in this paper.

A magnetostrictive tactile sensor based on Galfenol [(Fe₈₃Ga₁₇)_99.4B_0.6] is designed and studied for surface depth measurement. The optimal structure of the sensor is determined by experiment and theory. The test platforms for static and dynamic characteristics are set up. The static and the dynamic sensing performance of the sensor are studied experimentally.

The sensor can detect 0–2 mm depth change with a sensitivity of 91.5 mV/mm. A resolution of 50 µm can be achieved in the depth direction. In 50 cycles of loading and unloading tests, the maximum error of the sensor output voltage amplitude is only 2.23%.

The sensor can measure the depth information of object surface precisely with good repeatability through sliding motion and provide reference for object surface topography detection.

The noise measurement on magnetoresistive (MR) sensors is generally conducted by techniques including single-channel data sampling and fast Fourier transform (FFT) analysis as well as two-channel cross-correlation. The single-channel method is easy to implement and is widely used in the noise measurement on MR sensors, whereas the two-channel method can only eliminate part of the system noise. This study aims to address two key issues affecting measurement accuracy: calibration of the measurement system and the elimination of system noise.

The system is calibrated by using a low-noise metal film resistor in that the system noise is eliminated through power spectrum subtraction. Noise measurement and analysis are conducted for both thermal noise and detectivity of magnetic tunnel junction (MTJ) sensor.

The thermal noise measurement error is less than 2%. The detectivity of the MTJ sensor reaches 27 pT/Hz^1/2 at 2 kHz.

This study provides a more practical solution for noise measurement and system calibration on MR sensors with a bias voltage and magnetic field.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

Data traffic through wireless communication is significantly increasing, resulting in the frequency of streaming applications as various formats and the evolution of the Internet of Things (IoT), such as virtual reality, edge device based transportation and surveillance systems. Growth in kind of applications resulted in increasing the scope of wireless communication and allocating a spectrum, as well as methods to decrease the intervention between nearby-located wireless links functioning on the same spectrum bands and hence to proliferation for the spectral efficiency. Recent advancement in drone technology has evolved quickly leading on board sensors with increased energy, storage, communication and processing capabilities. In future, the drone sensor networks will be more common and energy utilization will play a crucial role to maintain a fully functional network for the longest period of time. Envisioning the aerial drone network, this study proposes a robust high level design of algorithms for the drones (group coordination). The proposed design is validated with two algorithms using multiple drones consisting of various on-board sensors. In addition, this paper also discusses the challenges involved in designing solutions. The result obtained through proposed method outperforms the traditional techniques with the transfer rate of more than 3 MB for data transfer in the drone with coordination

Fair Scheduling Algorithm (FSA) using a queue is a distributed slot assignment algorithm. The FSA executes in rounds. The duration of each round is dynamic based upon the delay in the network. FSA prevents the collision by ensuring that none of the neighboring node gets the same slot. Nodes (Arivudainambi et al., 2019) which are separated by two or more hopes can get assigned in the same slot, thereby preventing the collision. To achieve fairness at the scheduling level, the FSA maintains four different states for each node as IDLE, REQUEST, GRANT and RELEASE.

A multi-unmanned aerial vehicle (UAV) system can operate in both centralized and decentralized manner. In a centralized system, the ground control system will take care of drone data collection, decisions on navigation, task updation, etc. In a decentralized system, the UAVs are unambiguously collaborating on various levels as mentioned in the centralized system to achieve the goal which is represented in Figure 2.

However, the multi-UAVs are context aware in situations such as environmental observation, UAV–UAV communication and decision-making. Independent of whether operation is centralized or decentralized, this study relates the goals of the multi-UAVs are sensing, communication and coordination among other UAVs, etc. Figure 3 shows overall system architecture.

The individual events attempts in the UAV’s execution are required to complete the mission in superlative manner which affects in every multi UAV system. This multi UAV systems need to take a steady resolute on what way UAV has to travel and what they need to complete to face the critical situations in changing of environments with the uncertain information. This coordination algorithm has certain dimensions including events that they needs to resolute on, the information that they used to make a resolution, the resolute making algorithm, the degree of decentralization. In multi UAV systems, the coordinated events ranges from lower motion level.

This study has proposed a novel self-organizing coordination algorithm for multi-UAV systems. Further, the experimental results also confirm that is robust to form network at ease. The testbed for this simulation to sensing, communication, evaluation and networking. The algorithm coordination has to testbed with multi UAVs systems. The two scheduling techniques has been used to transfer the packets using done network. The self-organizing algorithm (SOA) with fair scheduling queue outperforms the weighted queue scheduling in the transfer rate with less loss and time lag. The results obtained through from Figure 10 clearly indicates that the fair queue scheduling with SOA have several advantages over weighted fair queue in different parameters.