Application Of Multiple Sensors Research Articles

A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review.

Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed.

Decision fusion of two sensors object classification based on the evidential reasoning rule

The application of multiple sensors for object classification is commonly used in unmanned intelligent systems such as autonomous driving and robots. Current researches based on evidential reasoning rules mainly consider multiple sensor fusion. The reliability is determined by the decisions of the majority of sensors and the weight is determined by historical accuracy. However, the existing researches using the evidential reasoning rule are not applicable when there are only two sensors working in some situations. This paper proposes a two sensors decision fusion method for object classification based on the evidential reasoning rule. The reliability of sensors is calculated with the Logistic model based on the differences of the classification decisions in a certain time span and the adaptive weights of sensors are calculated based on the coefficient of variation to adapt to different environments. The final decision is drawn out by fusing the classification decisions of two sensors based on the fusion rules of evidential reasoning rule. Comparative experimental studies of object classification decision fusion in autonomous driving are carried out with the Nuscenes dataset and the Waymo dataset. The results show that the method proposed can effectively improve the accuracy of the fusion when there are only two sensors.

Micro Service based Sensor Integration Efficiency and Feasibility in the Semiconductor Industry

The semiconductor industry is strongly increasing the production capacities and the product portfolio for a wide range of applications that are needed in the worldwide supply chains e.g. the automotive, computer and security industry. The complex manufacturing processes require more automation, dig- italisation and IoT frameworks, especially for highly automated semiconductor manufacturing plants. Over the last years, this industry spent much effort to control highly sensitive materials in production by product monitoring using advanced process control by various sensors in production. Nevertheless, until today, sensor integration, especially for such sensors that are not supported by the equipment vendors, is time-consuming and complicated. This article aims to use a micro-service-based approach by Eclipse Arrowhead as an open-source microservice architecture and implementation platform [1]. This architecture is an easy and powerful framework that can be used for multiple sensor applications to control the manufacturing material flow in a modern semiconductor plant with a high product mix. The article describes how the engineering process was designed, the architecture of the use case and the main benefits in the operational business are shown.

Investigation the influence of miniaturized RFID tag sensor on coupling effect

Purpose The skin and skeleton of aircraft are connected by adhesives or rivets to bear and transfer aerodynamic load. It is easy for crack and fracture damage to occur under the action of cyclic load, thus reducing aircraft bearing capacity/integrity and causing serious security risks. Therefore, it is particularly important that passive wireless radio frequency identification (RFID) sensors be used for the health monitoring of aircraft skin in its whole life cycle. This paper aims to investigate the influence of miniaturization on the coupling effect between RFID tag sensors. Design/methodology/approach Two groups of crack sensing systems based on RFID tags were designed. Gain and mutual impedance of sensor tags were analyzed via mode analysis. The reliability of crack detection of both sensing systems was compared using a preset experimental scheme. Findings Miniaturized antennas can reduce edge influence and the coupling effect. Gain and mutual impedance decrease with the increase in distance between dual tags. Backscatter power shows a decreasing trend and threshold power to activate tags in reader antenna increases. Results show that the miniaturization of size is more suitable for the application of multiple sensors. Originality/value By comparing two groups of sensing systems, the consistency of crack detection sensitivity is better when small tags are placed in parallel, which provides a theoretical basis for the application of small, passive and densely distributed crack sensors in the future.

Development of an Automatic Vehicular Heatstroke Detection System

The cases of children being left in a car and died of heatstroke are on the rise every year. Car manufacturers have not implemented any sort of alert system that could prevent these unfortunate events from happening. There are many baby car seat alert systems available in the market, however, they are mostly inconsistent and unreliable. There is a need for more effective and efficient alert system to remind the users of their forgotten child. This paper aims to provide solutions to caretakers through application of multiple sensors for integration of a child detection system and also to discover the best placement of the sensors for a more effective system. The selection method is based on experimental setup with a test subject which is a human being. A prototype for the detection system is fabricated and results show a combination of ultrasonic and motion sensors produces the best results. The best position to place the ultrasonic and motion sensor is determined to be above the child seat and in the middle of the car respectively. The prototype of the detection and alert system is validated via a set of assessments to determine its accuracy, adaptability and reliability.

Multi-sensor Integrated System for Reverse Engineering

Application of multiple sensors in Reverse Engineering (RE) has been effective approach to meet increasing demands of both complexity and accuracy. However, methodology to plan RE steps using systems combining different sensors has been a serious challenge. This paper presents hybrid system that integrates laser line scanning probe and touch trigger probe of coordinate measuring machine for RE of complex part. As a result of integration, this system utilizes strength of one system to overcome limitation of other. In this paper, RE methodology using hybrid system has been described through a part case study. The primary objective of this paper is to retrieve lost 2D drawings as well as damaged portion of mechanical part efficiently and accurately using hybrid system.

Silicon-on-insulator based ZnO nanowire photodetector

The authors present here a technologically easy process to electrically contact ensembles of ZnO nanowires on silicon-on-insulator substrates for multiple sensor applications. Microtrenches defined by standard photolithography and etching processes were bridged by ZnO nanowires. The ZnO nanowires grown by a high temperature process show excellent crystalline quality as confirmed by photoluminescence. These wires connecting the opposite sides of the microtrenches were investigated here as solar-blind photosensitive detectors, but may equally well serve for any other sensing application, where the ZnO conductivity is altered by the attachment of specific gases, proteins, etc. The straightforward design allows for an easy integration into CMOS processes.

MEASUREMENT METHOD FOR SENSITIVITY ANALYSIS OF PROXIMITY SENSOR AND SENSOR ANTENNA INTEGRATION IN A HANDHELD DEVICE

A method for measuring the sensitivity of a capacitive proximity sensor and an application using the sensor as a proximity detector in mobile phone antennas is presented. 2D sensor data plots were physically more exact for tuning sensor placement. 3D sensor data plots were suitable for sensor intensity comparison, highlighting sensor difierences in multiple sensor applications and efiects in sensor's output due to shadowing mechanical objects. The antenna proximity sensor was measured and optimised with sensitivity measurements. In a PIFA application the antenna load could be detected from both sides and from above the antenna on a scale of 4:03 ¢ 10 i14 F to 4:33 ¢ 10 i14 F. The cases present all possible positions of holding a phone used in either the \calling or \browsing mode. The method and the application emphasise the physical sensitivity and electrical flelds of the sensor. The characteristics can be further improved by using other sensor types, sensor data fusion and advanced imitation of multisensory spatial interaction by humans and animals.

Reduced State Estimator For Systems With Parametric Inputs

A reduced state estimator is derived for systems with bounded parameters as inputs. Optimal filter gains are derived for minimizing the total covariance of the estimation error due to measurement noise and parameter uncertainty. It is shown that these filter gains for a two-state system with a Gaussian parameter satisfy the Kalata relation in steady state. Equations are also derived for optimally filtering measurements in arbitrary time order. This reduced state estimator offers novelties over a traditional Kalman filter in its application to the class of problems considered. The total error covariance, which is minimized, makes no use of plant noise. Furthermore, the filter is easier to optimize in high dimensional and multiple sensor applications as well as in processing out-of-sequence measurements.

Closed-Loop Control of MBE Using an Integrated Multi-Sensor System

ABSTRACTThe use of in situ sensors to achieve real-time control of molecular beam epitaxy (MBE) is a rapidly evolving technology that promises to revolutionize MBE in terms of process repeatability and first-pass success, and consequently to improve the overall yield and reduce the cost of the process. To achieve robust real-time control of MBE, we have constructed a multiple-sensor control system comprising in situ sensors for substrate temperature, for effusion cell fluxes, and for the epitaxial layer composition and thickness, along with advanced software to manage the sensor information and execute sensor-feedback control algorithms. This system has been used to grow a number of different III-V semiconductor materials and device structures, including heterojunction bipolar transistors, resonant tunneling devices, and mid-IR lasers. In the present paper, we present results demonstrating control and regulation of substrate temperature and epitaxial layer composition during the growth of lattice-matched InGaAs and InA1As on InP. The control algorithms and software used in the system are described, and we discuss how the synergistic application of multiple sensors allows the regime of composition control to be expanded beyond what would be possible with only a single composition sensor.