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Journal articles on the topic 'Sensor'
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1
Yu, Jerry. "Deflation-activated receptors, not classical inflation-activated receptors, mediate the Hering-Breuer deflation reflex." Journal of Applied Physiology 121, no. 5 (November 1, 2016): 1041–46. http://dx.doi.org/10.1152/japplphysiol.00903.2015.
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Many airway sensory units respond to both lung inflation and deflation. Whether those responses to opposite stimuli come from one sensor (one-sensor theory) or more than one sensor (multiple-sensor theory) is debatable. One-sensor theory is commonly presumed in the literature. This article proposes a multiple-sensor theory in which a sensory unit contains different sensors for sensing different forces. Two major types of mechanical sensors operate in the lung: inflation- and deflation-activated receptors (DARs). Inflation-activated sensors can be further divided into slowly adapting receptors (SARs) and rapidly adapting receptors (RARs). Many SAR and RAR units also respond to lung deflation because they contain DARs. Pure DARs, which respond to lung deflation only, are rare in large animals but are easily identified in small animals. Lung deflation-induced reflex effects previously attributed to RARs should be assigned to DARs (including pure DARs and DARs associated with SARs and RARs) if the multiple-sensor theory is accepted. Thus, based on the information, it is proposed that activation of DARs can attenuate lung deflation, shorten expiratory time, increase respiratory rate, evoke inspiration, and cause airway secretion and dyspnea.
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Abbas, Jabbar, Amin Al-Habaibeh, and Dai Zhong Su. "Sensor Fusion for Condition Monitoring System of End Milling Operations." Key Engineering Materials 450 (November 2010): 267–70. http://dx.doi.org/10.4028/www.scientific.net/kem.450.267.
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This paper describes the utilisation of multi sensor fusion model using force, vibration, acoustic emission, strain and sound sensors for monitoring tool wear in end milling operations. The paper applies the ASPS approach (Automated Sensor and Signal Processing Selection) method for signal processing and sensor selection [1]. The sensory signals were processed using different signal processing methods to create a wide range of Sensory Characteristic Features (SCFs). The sensitivity of these SCFs to tool wear is investigated. The results indicate that the sensor fusion system is capable of detecting machining faults in comparison to a single sensor using the suggested approach.
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Guo, Yixuan, and Gaoyang Liang. "Perceptual Feedback Mechanism Sensor Technology in e-Commerce IoT Application Research." Journal of Sensors 2021 (September 28, 2021): 1–12. http://dx.doi.org/10.1155/2021/3840103.
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With the development of sensor technology and the Internet of Things (IoT) technology, the trend of miniaturization of sensors has prompted the inclusion of more sensors in IoT, and the perceptual feedback mechanism among these sensors has become particularly important, thus promoting the development of multiple sensor data fusion technologies. This paper deeply analyzes and summarizes the characteristics of sensory data and the new problems faced by the processing of sensory data under the new trend of IoT, deeply studies the acquisition, storage, and query of sensory data from the sensors of IoT in e-commerce, and proposes a ubiquitous storage method for massive sensory data by combining the sensory feedback mechanism of sensors, which makes full use of the storage resources of IoT storage network elements and maximally meets the massive. In this paper, we propose a ubiquitous storage method for massive sensing data, which makes full use of the storage resources of IoT storage network elements to maximize the storage requirements of massive sensing data and achieve load-balanced data storage. In this paper, starting from the overall development of IoT in recent years, the weak link of intelligent information processing is reinforced based on the sensory feedback mechanism of sensor technology.
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Hasegawa, Hiroaki, Yosuke Suzuki, Aiguo Ming, Masatoshi Ishikawa, and Makoto Shimojo. "Robot Hand Whose Fingertip Covered with Net-Shape Proximity Sensor - Moving Object Tracking Using Proximity Sensing -." Journal of Robotics and Mechatronics 23, no. 3 (June 20, 2011): 328–37. http://dx.doi.org/10.20965/jrm.2011.p0328.
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Occlusion in several millimeters from an object to be grasped made it difficult for a vision-sensor-based approach to detect relative positioning between this object and robot fingers joint grasping. The proximity sensor we proposed detects the object at a near range very effectively. We developed a thin proximity sensor sheet to cover the 3 fingers of a robot hand. Integrating sensors and hand control, we implemented an objecttracking controller. Using proximity sensory signals, the controller coordinates wrist positioning based on palm proximity sensors and grasping from fingertip sensors, enabling us to track and capture moving objects.
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Suranthiran, Sugathevan, and Suhada Jayasuriya. "Signal Conditioning With Memory-Less Nonlinear Sensors." Journal of Dynamic Systems, Measurement, and Control 126, no. 2 (June 1, 2004): 284–93. http://dx.doi.org/10.1115/1.1766030.
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Proposed in this paper is an off-line signal conditioning scheme for memoryless nonlinear sensors. In most sensor designs, a linear input-output response is desired. However, nonlinearity is present in one form or another in almost all real sensors and therefore it is very difficult if not impossible to achieve a truly linear relationship. Often sensor nonlinearity is considered a disadvantage in sensory systems because it introduces distortion into the system. Due to the lack of efficient techniques to deal with the issues of sensor nonlinearity, primarily nonlinear sensors tend to be ignored. In this paper, it is shown that there are certain advantages of using nonlinear sensors and nonlinear distortion caused by sensor nonlinearity may be effectively compensated. A recursive algorithm utilizing certain characteristics of nonlinear sensor functions is proposed for the compensation of nonlinear distortion and sensor noise removal. A signal recovery algorithm that implements this idea is developed. Not having an accurate sensor model will result in errors and it is shown that the error can be minimized with a proper choice of a convergence accelerator whereby stability of the developed algorithm is established.
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Han, Yan. "The Building of Optical Fiber Network System Using Hetero-Core Fiber Optic Sensors." Advanced Materials Research 571 (September 2012): 342–46. http://dx.doi.org/10.4028/www.scientific.net/amr.571.342.
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We proposed a novel optical sensory nerve network using pulse switch sensors. The pulse switch sensor generates light loss similar to pulse signals only when ON/OFF states change. Therefore, it has less influence on communications quality compared with conventional switch sensor modules as sensor multiplicity increases. Our simulated results demonstrated that the proposed system can improve sensor multiplicity while maintaining the communications and measuring performance with the same quality as a conventional system by appropriately adjusting the initial loss of the pulse switch sensors. In particular, where ON/OFF time intervals follow exponential distributions with mean values of 5 and 300 s, respectively, the insertion loss of hetero-core segments inserted into pulse switch sensors is 0.3 dB, and the pulse switch sensors have curvature from 0.05 to 0.18. Under these conditions, our enhanced system can increase sensor multiplicity to 23 while maintaining link availability of almost 100%, a distinction error ratio of less than 1%, and a duplicated error ratio of about 0.5%.
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Jalil Piran, Mohammad, Amjad Ali, and Doug Young Suh. "Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/439272.
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In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unified interpretation. The best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and definitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET). In the proposed technique, we considered four input sensor readings (antecedents) and one output (consequent). The employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, The Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash_Severity is considered as the consequent variable. The processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes.
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Chen, Tzung-Shi, Jen-Jee Chen, Xiang-You Gao, and Tzung-Cheng Chen. "Mobile Charging Strategy for Wireless Rechargeable Sensor Networks." Sensors 22, no. 1 (January 4, 2022): 359. http://dx.doi.org/10.3390/s22010359.
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In a wireless sensor network, the sensing and data transmission for sensors will cause energy depletion, which will lead to the inability to complete the tasks. To solve this problem, wireless rechargeable sensor networks (WRSNs) have been developed to extend the lifetime of the entire network. In WRSNs, a mobile charging robot (MR) is responsible for wireless charging each sensor battery and collecting sensory data from the sensor simultaneously. Thereby, MR needs to traverse along a designed path for all sensors in the WRSNs. In this paper, dual-side charging strategies are proposed for MR traversal planning, which minimize the MR traversal path length, energy consumption, and completion time. Based on MR dual-side charging, neighboring sensors in both sides of a designated path can be wirelessly charged by MR and sensory data sent to MR simultaneously. The constructed path is based on the power diagram according to the remaining power of sensors and distances among sensors in a WRSN. While the power diagram is built, charging strategies with dual-side charging capability are determined accordingly. In addition, a clustering-based approach is proposed to improve minimizing MR moving total distance, saving charging energy and total completion time in a round. Moreover, integrated strategies that apply a clustering-based approach on the dual-side charging strategies are presented in WRSNs. The simulation results show that, no matter with or without clustering, the performances of proposed strategies outperform the baseline strategies in three respects, energy saving, total distance reduced, and completion time reduced for MR in WSRNs.
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R, Keerthana, Lavanya S, Negaa Vaidheesvari M, Saranya B, and Yashini M. "Smart Walker Instrumentation Using Hand Gestures." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 3891–95. http://dx.doi.org/10.22214/ijraset.2023.49316.
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Abstract: The passive walker devices currently in use may steer or brake spontaneously, requiring the user to urge them ahead. This project creates a smart walker system with sensors and actuators for enhanced support and assistance. Here, the user controls the walker with hand gestures. Better physical support, sensory support, cognitive support, health monitoring, and human-machine interface are the key benefits. The method incorporates gyroscopes that measure the angles of hand movements and start the smart walker moving in the user's chosen directions. The temperature sensor, EMG sensor and gyroscope are used, to measure the health factors such as temperature, muscle activity and leg position angles and hand angles. Arduino is used as a control unit. It is mostly applied for the use of senior persons and people with lower limb disabilities during the rehabilitation stage.
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Yu, Jerry. "Spectrum of myelinated pulmonary afferents (III) cracking intermediate adapting receptors." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 319, no. 6 (December 1, 2020): R724—R732. http://dx.doi.org/10.1152/ajpregu.00136.2020.
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Conventional one-sensor theory (one afferent fiber connects to a single sensor) categorizes the bronchopulmonary mechanosensors into the rapidly adapting receptors (RARs), slowly adapting receptors (SARs), or intermediate adapting receptors (IARs). RARs and SARs are known to sense the rate and magnitude of mechanical change, respectively; however, there is no agreement on what IARs sense. Some investigators believe that the three types of sensors are actually one group with similar but different properties and IARs operate within that group. Other investigators (majority) believe IARs overlap with the RARs and SARs and can be classified within them according to their characteristics. Clearly, there is no consensus on IARs function. Recently, a multiple-sensor theory has been advanced in which a sensory unit may contain many heterogeneous sensors, such as both RARs and SARs. There are no IARs. Intermediate adapting unit behavior results from coexistence of RARs and SARs. Therefore, the unit can sense both rate and magnitude of changes. The purpose of this review is to provide evidence that the multiple-sensor theory better explains sensory unit behavior.
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Qiu, Hao, Gaoming Huang, and Jun Gao. "Centralized multi-sensor multi-target tracking with labeled random finite set." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 4 (August 6, 2016): 669–76. http://dx.doi.org/10.1177/0954410016641447.
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Tracking multiple objects with multiple sensors is widely recognized to be much more complex than the single-sensor scenario. This contribution proposes a computationally tractable multi-sensor multi-target tracker. Based on Bayes equation and multi-senor observation model, a new corrector for multi-senor is derived. To lower the complexity of update operation, a parallel track-to-measurement association strategy is applied to the corrector. Hypotheses truncation scheme along with first-moment approximation of multi-target density are also employed to improve the tracking efficiency. The tracker is applied to a couple-sensor scenario. Experiment results validate the advantages of proposed method compared to the standard single-sensor δ-generalized labeled multi-Bernoulli filter and the iterated-corrector probability hypothesis density filter.
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Chan, Tung Jung, Ching Mu Chen, and Tsair Rong Chen. "A Forwarding Station Integrated with Optimal Cluster Number Selection in Wireless Sensor Networks." Applied Mechanics and Materials 201-202 (October 2012): 745–48. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.745.
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In wireless sensor networks, power consumption is the most important issue. That is wireless sensors are normally deployed into unattended places where power of sensors is hard to be charged. Indeed, the network lifetime of wireless sensor networks equipped with city power or deployed into attended place is much longer than those wireless sensors equipped with batteries. In general, wireless sensor nodes are connected together and become a network after deployed into certain places. With the certain range places that wireless senor nodes deployed into, finding the optimal clusters can increase the entire network lifetime. Also, adding the forwarding station extends the network lifetime. Therefore, this paper proposes the integration of both the forwarding station and optimal clusters in ad-hoc wireless sensor networks. Simulation results show that the entire network lifetime proposed is extended in this paper compared to both optimal cluster number selection and normal forwarding station.
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Hardman, David, Thomas George Thuruthel, Antonia Georgopoulou, Frank Clemens, and Fumiya Iida. "3D Printable Soft Sensory Fiber Networks for Robust and Complex Tactile Sensing." Micromachines 13, no. 9 (September 17, 2022): 1540. http://dx.doi.org/10.3390/mi13091540.
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The human tactile system is composed of multi-functional mechanoreceptors distributed in an optimized manner. Having the ability to design and optimize multi-modal soft sensory systems can further enhance the capabilities of current soft robotic systems. This work presents a complete framework for the fabrication of soft sensory fiber networks for contact localization, using pellet-based 3D printing of piezoresistive elastomers to manufacture flexible sensory networks with precise and repeatable performances. Given a desirable soft sensor property, our methodology can design and fabricate optimized sensor morphologies without human intervention. Extensive simulation and experimental studies are performed on two printed networks, comparing a baseline network to one optimized via an existing information theory based approach. Machine learning is used for contact localization based on the sensor responses. The sensor responses match simulations with tunable performances and good localization accuracy, even in the presence of damage and nonlinear material properties. The potential of the networks to function as capacitive sensors is also demonstrated.
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Singh, Ravinder, and Kuldeep Singh Nagla. "Comparative analysis of range sensors for the robust autonomous navigation – a review." Sensor Review 40, no. 1 (October 29, 2019): 17–41. http://dx.doi.org/10.1108/sr-01-2019-0029.
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Purpose The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment. Design/methodology/approach Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot. Findings This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot. Originality/value This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.
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Chen, D., X. Zhang, N. Chen, J. Yang, and J. Gong. "GEOSPATIAL SENSOR WEB ADAPTOR FOR INTEGRATING DIVERSE INTERNET OF THINGS PROTOCOLS WITHIN SMART CITY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2020 (August 3, 2020): 115–21. http://dx.doi.org/10.5194/isprs-annals-v-4-2020-115-2020.
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Abstract. In recent years, the multi-scale comprehensive perception is central to smart city development. We propose an "adaptor" for geospatial sensor web as an integrated sensory system that can integrate access to geodetic equipment based on the Internet of Things technology with multiple platforms and protocols. At the same time, the acquisition, fusion, and processing of sensory resources can perform. The geospatial adaptor can access and process sensors of different IoT protocols to different conditions simultaneously. Grace to this geospatial adaptor, a considerable number of the sensor based on IoT in the community, can achieve distributed access, ensuring the better robustness of the geospatial sensor web. This paper describes the system architecture of the geospatial sensor web adapter. Furthermore, from the perspective of protocol access, it introduces the access capabilities of geospatial sensor web adapter to the standard IoT interface protocols. By comparing the geospatial sensor web adapter with traditional observation methods by experiments and acquisition of test data. The results show that the geospatial sensor web adapter can achieve powerful access capabilities and network stability, and it is a better solution for heterogeneous sensing platform access in smart cities.
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Bílek, Jiří, Ondřej Bílek, Petr Maršolek, and Pavel Buček. "Ambient Air Quality Measurement with Low-Cost Optical and Electrochemical Sensors: An Evaluation of Continuous Year-Long Operation." Environments 8, no. 11 (October 27, 2021): 114. http://dx.doi.org/10.3390/environments8110114.
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Sensor technology is attractive to the public due to its availability and ease of use. However, its usage raises numerous questions. The general trustworthiness of sensor data is widely discussed, especially with regard to accuracy, precision, and long-term signal stability. The VSB-Technical University of Ostrava has operated an air quality sensor network for more than two years, and its large sets of valid results can help in understanding the limitations of sensory measurement. Monitoring is focused on the concentrations of dust particles, NO2, and ozone to verify the impact of newly planted greenery on the reduction in air pollution. The sensor network currently covers an open field on the outskirts of Ostrava, between Liberty Ironworks and the nearby ISKO1650 monitoring station, where some of the worst air pollution levels in the Czech Republic are regularly measured. In the future, trees should be allowed to grow over the sensors, enabling assessment of the green barrier effect on air pollution. As expected, the service life of the sensors varies from 1 to 3 years; therefore, checks are necessary both prior to the measurement and regularly during operation, verifying output stability and overall performance. Results of the PMx sensory measurements correlated well with the reference method. Concentration values measured by NO2 sensors correlated poorly with the reference method, although timeline plots of concentration changes were in accordance. We suggest that a comparison of timelines should be used for air quality evaluations, rather than particular values. The results showed that the sensor measurements are not yet suitable to replace the reference methods, and dense sensor networks proved useful and robust tools for indicative air quality measurements (AQM).
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Mrozek, Piotr, Ewa Gorodkiewicz, Paweł Falkowski, and Bogusław Hościło. "Sensitivity Analysis of Single- and Bimetallic Surface Plasmon Resonance Biosensors." Sensors 21, no. 13 (June 25, 2021): 4348. http://dx.doi.org/10.3390/s21134348.
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Comparative analysis of the sensitivity of two surface plasmon resonance (SPR) biosensors was conducted on a single-metallic Au sensor and bimetallic Ag–Au sensor, using a cathepsin S sensor as an example. Numerically modeled resonance curves of Au and Ag–Au layers, with parameters verified by the results of experimental reflectance measurement of real-life systems, were used for the analysis of these sensors. Mutual relationships were determined between ∂Y/∂n components of sensitivity of the Y signal in the SPR measurement to change the refractive index n of the near-surface sensing layer and ∂n/∂c sensitivity of refractive index n to change the analyte’s concentration, c, for both types of sensors. Obtained results were related to experimentally determined calibration curves of both sensors. A characteristic feature arising from the comparison of calibration curves is the similar level of Au and Ag–Au biosensors’ sensitivity in the linear range, where the signal of the AgAu sensor is at a level several times greater. It was shown that the influence of sensing surface morphology on the ∂n/∂c sensitivity component had to be incorporated to explain the features of calibration curves of sensors. The shape of the sensory surface relief was proposed to increase the sensor sensitivity at low analyte concentrations.
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Hausmann, M., L. Häfner, and E. Kirchner. "A Procedure Model for the Systematic Sensor Selection and Integration into Technical Systems." Proceedings of the Design Society 2 (May 2022): 445–54. http://dx.doi.org/10.1017/pds.2022.46.
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AbstractNew sensor solutions are under development in the context of digitalization in order to integrate sensory functions into systems. When integrating sensors, the three domains of mechanical, electrical and information engineering must be considered. This results in complex development processes that require suitable procedure models. However, specific procedure models for sensor selection and integration are missing. This contribution proposes a procedure model for sensor selection and integration on the basis of the Munich Procedure Model (MPM) and gives an outlook on open research questions.
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Yang, Le, Han Wang, Jiajian Zheng, Xin Duan, and Qishuo Cheng. "Research and Application of Visual Object Recognition System Based on Deep Learning and Neural Morphological Computation." International Journal of Computer Science and Information Technology 2, no. 1 (March 4, 2024): 10–17. http://dx.doi.org/10.62051/ijcsit.v2n1.02.
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The development of advanced optoelectronic vision sensors for high-level image recognition and data preprocessing is poised to accelerate the progress of machine vision and mobile electronic technology. Compared to traditional sensory computing methods, such as analog-to-digital signal conversion and digital logic computation tasks (i.e., Von Neumann computing), neural morphological vision computing can significantly improve energy efficiency and data processing speed by minimizing unnecessary raw data transmission between front-end photosensitive sensors and back-end processors. Neural morphological vision sensors are typically designed for tasks such as denoising, edge enhancement, spectral filtering, and visual information recognition. These methods can be categorized into approaches using near-sensor and sensor-internal computing processors based on whether preprocessing can be performed in situ. In near-sensor computing approaches, the image sensor for capturing visual information and the memory computing processor for preprocessing captured images are separate. A memory computing processor can simultaneously perform memory and computing tasks based on analog memory functions. Neural morphological vision sensors for in-sensor computing can be constructed using single-element image sensors, enabling both the reception of visual information and the execution of memory computing processes to be achieved in the same device. This represents an ideal scenario for future artificial intelligence machines and mobile electronic devices in visual computing systems.
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Ishikawa, Masatoshi. "Active Sensor System Using Parallel Processing Circuits." Journal of Robotics and Mechatronics 5, no. 1 (February 20, 1993): 31–37. http://dx.doi.org/10.20965/jrm.1993.p0031.
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In this paper, an active sensor system using parallel processing circuits is proposed and its characteristics are discussed. From the perspective of a model of active touch sensory processing mechanism, the system uses information of efferent copy and internal actuator model in order to generate active motions from the local pattern information detected by local pattern sensors, such as tactile sensors. In addition, an experimental system and its basic experimental results are described. The experimental system is a sensor system for active perception of the shape of two-dimensional objects by tracing the edge of the objects. The system realizes both high speed processing of the local pattern and real-time control of the actuator.
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Lee, Young Sup, Dong Jin Yoon, Sang Il Lee, and Jaehwa Kwon. "An Active Piezo Array Sensor for Elastic Wave Detection." Key Engineering Materials 297-300 (November 2005): 2004–9. http://dx.doi.org/10.4028/www.scientific.net/kem.297-300.2004.
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This paper describes an array sensor of piezoceramic PZT discs with flexible covering layers, which is designed to detect surface elastic waves in structures, such as Rayleigh waves. The sensor is distinguished from conventional “passive” sensors for elastic waves detection because it possesses an ability to actuate an “active” pulse. This indicates that the function of active pulse generation ensures the diagnosis of the structures, where the sensor attached or embedded into, can be accomplished in a smart way including an easy inspection of faults. Actually the sensor has been inspired from human sensory systems in order to apply for smart structure sensing. They utilized 6mm diameter and 0.25mm thick PZT discs for the active array sensor. The performance of the sensor was demonstrated at various experiments of some metal and composite structures that the sensor can be applied for the health monitoring of the advanced smart structure system.
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A. Moshizi, Sajad, Christopher J. Pastras, Shuhua Peng, Shuying Wu, and Mohsen Asadnia. "Artificial Hair Cell Sensor Based on Nanofiber-Reinforced Thin Metal Films." Biomimetics 9, no. 1 (January 2, 2024): 18. http://dx.doi.org/10.3390/biomimetics9010018.
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Engineering artificial mechanosensory hair cells offers a promising avenue for developing diverse biosensors spanning applications from biomedicine to underwater sensing. Unfortunately, current artificial sensory hair cells do not have the ability to simultaneously achieve ultrahigh sensitivity with low-frequency threshold detection (e.g., 0.1 Hz). This work aimed to solve this gap by developing an artificial sensory hair cell inspired by the vestibular sensory apparatus, which has such functional capabilities. For device characterization and response testing, the sensory unit was inserted in a 3D printed lateral semicircular canal (LSCC) mimicking the environment of the labyrinth. The sensor was fabricated based on platinum (Pt) thin film which was reinforced by carbon nanofibers (CNFs). A Pi-shaped hair cell sensor was created as the sensing element which was tested under various conditions of simulated head motion. Results reveal the hair cell sensor displayed markedly higher sensitivity compared to other reported artificial hair cell sensors (e.g., 21.47 mV Hz−1 at 60°) and low frequency detection capability, 0.1 Hz < f < 1.5 Hz. Moreover, like the LSCC hair cells in biology, the fabricated sensor was most sensitive in a given plane of rotational motion, demonstrating features of directional sensitivity.
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Cao, Rongtao, Jingyu Wu, Yang Yang, Mohan Wang, Yuqi Li, and Kevin P. Chen. "A High-Temperature Multipoint Hydrogen Sensor Using an Intrinsic Fabry–Perot Interferometer in Optical Fiber." Photonics 10, no. 3 (March 8, 2023): 284. http://dx.doi.org/10.3390/photonics10030284.
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This paper presents a multiplexable fiber optic chemical sensor with the capability of monitoring hydrogen gas concentration at high temperatures up to 750 °C. The Pd-nanoparticle infused TiO2 films coated on intrinsic Fabry–Perot interferometer (IFPI) array were used as sensory films. Strains induced upon exposure to hydrogen with varied concentrations can be monitored by IFPI sensors. The fiber sensor shows a repetitive and reversible response when exposed to a low level (1–6%) of hydrogen gas. Uniform sensory behavior across all the sensing cavities is demonstrated and reported in this paper.
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Yeong, De Jong, Gustavo Velasco-Hernandez, John Barry, and Joseph Walsh. "Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review." Sensors 21, no. 6 (March 18, 2021): 2140. http://dx.doi.org/10.3390/s21062140.
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With the significant advancement of sensor and communication technology and the reliable application of obstacle detection techniques and algorithms, automated driving is becoming a pivotal technology that can revolutionize the future of transportation and mobility. Sensors are fundamental to the perception of vehicle surroundings in an automated driving system, and the use and performance of multiple integrated sensors can directly determine the safety and feasibility of automated driving vehicles. Sensor calibration is the foundation block of any autonomous system and its constituent sensors and must be performed correctly before sensor fusion and obstacle detection processes may be implemented. This paper evaluates the capabilities and the technical performance of sensors which are commonly employed in autonomous vehicles, primarily focusing on a large selection of vision cameras, LiDAR sensors, and radar sensors and the various conditions in which such sensors may operate in practice. We present an overview of the three primary categories of sensor calibration and review existing open-source calibration packages for multi-sensor calibration and their compatibility with numerous commercial sensors. We also summarize the three main approaches to sensor fusion and review current state-of-the-art multi-sensor fusion techniques and algorithms for object detection in autonomous driving applications. The current paper, therefore, provides an end-to-end review of the hardware and software methods required for sensor fusion object detection. We conclude by highlighting some of the challenges in the sensor fusion field and propose possible future research directions for automated driving systems.
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Henderson, Jeffrey, Joan Condell, James Connolly, Daniel Kelly, and Kevin Curran. "Reliability and Validity of Clinically Accessible Smart Glove Technologies to Measure Joint Range of Motion." Sensors 21, no. 5 (February 24, 2021): 1555. http://dx.doi.org/10.3390/s21051555.
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Capturing hand motions for hand function evaluations is essential in the medical field. For many allied health professionals, measuring joint range of motion (ROM) is an important skill. While the universal goniometer (UG) is the most used clinical tool for measuring joint ROM, developments in current sensor technology are providing clinicians with more measurement possibilities than ever. For rehabilitation and manual dexterity evaluations, different data gloves have been developed. However, the reliability and validity of sensor technologies when used within a smart device remain somewhat unclear. This study proposes a novel electronically controlled sensor monitoring system (ECSMS) to obtain the static and dynamic parameters of various sensor technologies for both data gloves and individual sensor evaluation. Similarly, the ECSMS was designed to closely mimic a human finger joint, to have total control over the joint, and to have an exceptionally high precision. In addition, the ECSMS device can closely mimic the movements of the finger from hyperextension to a maximum ROM beyond any person’s finger joint. Due to the modular design, the ECSMS’s sensor monitoring board is independent and extensible to include various technologies for examination. Additionally, by putting these sensory devices through multiple tests, the system accurately measures the characteristics of any rotary/linear sensor in and out of a glove. Moreover, the ECSMS tracks the movement of all types of sensors with respect to the angle values of finger joints. In order to demonstrate the effectiveness of sensory devices, the ECSMS was first validated against a recognised secondary device with an accuracy and resolution of 0.1°. Once validated, the system simultaneously determines real angles alongside the hand monitoring device or sensor. Due to its unique design, the system is independent of the gloves/sensors that were tested and can be used as a gold standard to realise more medical equipment/applications in the future. Consequently, this design greatly enhances testing measures within research contact and even non-contact systems. In conclusion, the ECSMS will benefit in the design of data glove technologies in the future because it provides crucial evidence of sensor characteristics. Similarly, this design greatly enhances the stability and maintainability of sensor assessments by eliminating unwanted errors. These findings provide ample evidence for clinicians to support the use of sensory devices that can calculate joint motion in place of goniometers.
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Zhang, Chang Jie, and Yu Liu. "A Sensor Grouping Method for Industrial Sensor Health Management." Applied Mechanics and Materials 621 (August 2014): 271–76. http://dx.doi.org/10.4028/www.scientific.net/amm.621.271.
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As many sensor networks have been deployed in industry monitoring area, the focus on sensor data quality has also increased. Sensor networks provide us with process details which we can utilize to help making decisions on process monitoring.In order to make meaningful decisions, the quality of the data produced by sensors must be validated. As we evaluate the status of a specific sensor, we may also regard the status of the related sensors. If a sensor’s data show some abnormal, but the sensors related to it didn’t, we may have much more confidence to believe that the sensor is malfunction. In our early study, the sensors grouping strategy is manual. In this paper, we proposed a sensor grouping algorithm, which combines both PCA decouple method and the K-means cluster method. Finally, a test has been made with real data from an oilfield.
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Gu, Junyi, Artjom Lind, Tek Raj Chhetri, Mauro Bellone, and Raivo Sell. "End-to-End Multimodal Sensor Dataset Collection Framework for Autonomous Vehicles." Sensors 23, no. 15 (July 29, 2023): 6783. http://dx.doi.org/10.3390/s23156783.
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Autonomous driving vehicles rely on sensors for the robust perception of their surroundings. Such vehicles are equipped with multiple perceptive sensors with a high level of redundancy to ensure safety and reliability in any driving condition. However, multi-sensor, such as camera, LiDAR, and radar systems raise requirements related to sensor calibration and synchronization, which are the fundamental blocks of any autonomous system. On the other hand, sensor fusion and integration have become important aspects of autonomous driving research and directly determine the efficiency and accuracy of advanced functions such as object detection and path planning. Classical model-based estimation and data-driven models are two mainstream approaches to achieving such integration. Most recent research is shifting to the latter, showing high robustness in real-world applications but requiring large quantities of data to be collected, synchronized, and properly categorized. However, there are two major research gaps in existing works: (i) they lack fusion (and synchronization) of multi-sensors, camera, LiDAR and radar; and (ii) generic scalable, and user-friendly end-to-end implementation. To generalize the implementation of the multi-sensor perceptive system, we introduce an end-to-end generic sensor dataset collection framework that includes both hardware deploying solutions and sensor fusion algorithms. The framework prototype integrates a diverse set of sensors, such as camera, LiDAR, and radar. Furthermore, we present a universal toolbox to calibrate and synchronize three types of sensors based on their characteristics. The framework also includes the fusion algorithms, which utilize the merits of three sensors, namely, camera, LiDAR, and radar, and fuse their sensory information in a manner that is helpful for object detection and tracking research. The generality of this framework makes it applicable in any robotic or autonomous applications and suitable for quick and large-scale practical deployment.
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Gabrieli, Gianmarco. "(General Student Poster Award Winner, 1st Place) Accelerated Estimation of Chemical and Sensory Liquid Attributes Using an AI-Assisted Electrochemical Electronic Tongue." ECS Meeting Abstracts MA2023-02, no. 65 (December 22, 2023): 3188. http://dx.doi.org/10.1149/ma2023-02653188mtgabs.
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Electronic tongues based on arrays of potentiometric sensors bears promises for enabling portable and fast analysis of complex liquids by leveraging low-selectivity and high-sensitivity of the inherent sensing materials. Thus, they have been studied and developed to target multiple applications, including analysis of chemical compositions or for untargeted quality control in the food industry. A key element to enable practical use of electronic tongues, however, has often been the analysis and interpretation of their combinatorial response due to the cross-sensitivity of the employed sensors. Indeed, disentangling the effect of multiple liquid constituents on the potentiometric response is the main associated challenge. The present contribution aims at studying the feasibility and accuracy of employing this class of sensors to both the quantification of multiple analytes in water as well as prediction of sensory attributes in coffee samples. A proof-of-concept system comprises an integrated array of miniaturized polymeric sensors and an electronic board records 15 differential voltages, produced by the interaction with both ionic and organic constituents of liquids, and can transmit them via Bluetooth to an external device. An automated pipeline performs pre-processing, hand-crafted feature extraction and training of machine learning models that can be then deployed on the cloud or edge device (e.g., smartphone). The same array can be then reconfigured to address a new specific task by leveraging new potentiometric data collection and applying the automated data analysis. In particular, the device presented herein employed 16 polymeric sensors that were electrodeposited on conventional electroless nickel immersion gold (ENIG) electrodes. The conductive polymers (PEDOT, PPy, PANI and PAPBA) were synthesized by chronoamperometry or cyclic voltammetry and enriched with doping agents for enhanced sensitivity. Differential voltages between these polymeric sensors were measured during the transition of the sensor array from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. Indeed, the use of low-selective sensors for potentiometric measurements does not require integration of reference electrodes, which are known to be unpractical for remote sensing applications. The analysis of the potentiometric response revealed deviations from linear sensitivities, showing non-Nernstian voltage trends when varying concentration of target analytes. Training data were obtained by alternatively immersing the sensor array in reference (120 s) and test (60 s) solutions continuously using an automated test rig. In addition to the conventional approach of measuring the equilibrium potential after a certain settling time, the complete evolution of the potentiometric signal in time could provide richer information that could be useful for building calibration models. Hence, hand-crafted features were extracted from time series recorded during sensor training in order to reduce the dimension of data and describe the complete voltage perturbation of the sensor during transition between reference and test solution. If exposed to enough “known liquid examples”, the sensor array can learn patterns to perform accelerated qualitative and quantitative analysis. The device has demonstrated enhanced discrimination of various mixtures and was proved able to predict beverage sensory properties after intensive training with samples with known sensory attributes. Firstly, the sensitivity to multiple ionic species was estimated in model mixtures obtained following an Orthogonal Experimental Design (OED) for a set of four metal ions, including Al3+, Cu2+, Na+ and Fe3+, and another set comprising Ca2+, Mg2+ and Na+. The former experiment demonstrated that non-linear regression models, such as a Random Forest of Extra Trees, can cope with non-linearity of the sensor response and yielded better performances than widely used multivariate regression model i.e., Multiple Linear Regression (MLR). The mean relative quantification error varied between 1% for Fe3+ and 44% for Na+ in the concentration range 1-10 mg/L. The second mixture set was used instead to unveil the cross-sensitive response of the sensor array, build a quantification model to predict major cations in mineral water and proving the importance of feature selection for data-driven sensors. Overall, the sensor showed comparable accuracy to ICP-MS (MRE 12-24%) but with a drastic reduction of cost and processing time. Finally, the same sensor array configuration was also used to test 12 coffee samples, which were also evaluated by a sensory panel through 5 taste attributes. Regression models were built to map instrument response to sensory data and Extra-Tree algorithm yielded the highest performances with a MRE varying from 8% to 21% depending on coffee sample and validation scheme. Thus, it was demonstrated that data-driven sensor arrays could be also valuable alternative tools for accelerated evaluation of beverage sensory characteristics and support food innovation processes. Figure 1
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Lee, Chao Yang, Fu Tian Lin, and Chu Sing Yang. "Mobile Sensor Navigation in Wireless Hybrid Sensor Networks." Advanced Materials Research 694-697 (May 2013): 1013–16. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1013.
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With recent advances in mobile platforms, hybrid sensor networks are becoming very popular technology. Mobile sensors can dynamically move to monitor uncovered areas and thus improve the coverage quality. Due to the obstacles may exist in the monitor fields, mobile sensors need to find an obstacle-free moving path for mobile sensor movement. However, in practical, sensors are difficult to obtain the geographic information of obstacles. Additionally, sensors have resource constraints. Hence, this work proposed an obstacle-free and geographic-free dispatch scheme (OGDS) for mobile sensor navigation with low computational complexity. The moving path for mobile sensor dispatch has obtained by using the Dynamic Source Routing protocol (DSR) protocol. Experimental results reveal that the proposed scheme can be efficiently executed.
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Hassanbeiglou, Alireza, Masoud Kalantari, Elaheh Mozaffari, Javad Dargahi, and József Kövecses. "A new tactile array sensor for viscoelastic tissues with time-dependent behavior." Sensor Review 35, no. 4 (September 21, 2015): 374–81. http://dx.doi.org/10.1108/sr-06-2014-656.
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Purpose – The purpose of this paper is to introduce a new tactile array sensor into the medical field to enhance current robotic minimally invasive surgery (RMIS) procedures that are still limited in scope and versatility. In this paper, a novel idea is proposed in which a tactile sensor array can measure rate of displacement in addition to force and displacement of any viscoelastic material during the course of a single touch. To verify this new array sensor, several experiments were conducted on a diversity of tissues from which it was concluded that this newly developed sensory offers definite and significant enhancements. Design/methodology/approach – The proposed array sensor is capable of extracting force, displacement and displacement rate in the course of a single touch on tissues. Several experiments have been conducted on different tissues and the array sensor to verify the concept and to verify the output of the sensor. Findings – It is shown that this new generation of sensors are required to distinguish the difference in hardness degrees of materials with viscoelastic behavior. Originality/value – In this paper, a new generation of tactile sensors is proposed that is capable of measuring indentation time in addition to force and displacement. This idea is completely unique and has not been submitted to any conference or journal.
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HUGHES, KEN, and N. RANGANATHAN. "MODELING SENSOR CONFIDENCE FOR SENSOR INTEGRATION TASKS." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 06 (December 1994): 1301–18. http://dx.doi.org/10.1142/s0218001494000656.
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This paper addresses the problem of determining the reliability of individual sensors in a multi-sensor robotic system in an unknown environment. The inherent difficulty in this problem is that the decision must be based solely upon the data from the sensors themselves. While some previous research has considered unstructured environments (see Refs. 1 and 2 for examples) little if any consideration has been given to totally unknown environments. This problem has usually been avoided by assuming that the sensors would not provide erroneous data or ignoring sensors when they appeared to provide erroneous data. We believe a more robust solution is to consider each sensor’s performance over time compared to other sensors, and from this determine a measure of confidence in each sensor. This allows sensors which temporarily provide erroneous data to be accommodated. A system which can determine the reliability of its sensors is more robust since it can wisely decide which sensors are most appropriate for a given task and can also determine whether sensor conflicts are the result of poorly performing sensors.
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Li, Guo Xin, Fei Lao, Bing Quan Huo, and Long Cheng. "Design of Fire Alarm System in Laboratory." Advanced Materials Research 912-914 (April 2014): 1232–35. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1232.
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Fire warning is a matter of concern in laboratory, this paper presents the design of distributed sensors fire warning system. The core idea is that a number of the bottom sensor collection terminals that consists of temperature and smoking sensors are evenly distributed in the laboratory; when there is a fire to happen, the bottom sensor collection terminals will send an alarming signal by the way of wireless communication to the middle layer alarming signal collection terminal, which starts a GPRS module to capture the scene and send the image to the senior monitoring management center. The senior manager receives an alarming image information, analysis and process, start the appropriate fire alarm system. After a year of testing and running, the system achieves the originally designed aim, and is reliable and stable.
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Heydarianasl, Mozhde. "Optimization of electrostatic sensor based on sensor separation." Sensor Review 39, no. 5 (September 16, 2019): 724–32. http://dx.doi.org/10.1108/sr-06-2018-0158.
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Purpose Electrostatic sensors are applied to measure velocity of solid particles in many industries because controlling the velocity particles improves product quality and process efficiency. The purpose of current paper is optimization of these sensors which is required to achieve maximum spatial sensitivity and minimum statistical error. Design/methodology/approach Different electrode of electrostatic sensors with different length, thickness and sensor separations were experimentally applied in laboratory. Then, correlation velocity, signal bandwidth and statistical error were calculated. Findings High sensor separation is a crucial factor because it would lead to increase signal similarity and decrease statistical error. This paper focuses on the effect of sensor separation on optimization of electrostatic sensors. Originality/value From observations, the optimal value for length, thickness and sensor separations was 0.6, 0.5 and 15 cm, respectively. Consequently, statistical error has improved by about 17 per cent. These results provided a significant basis of optimization of electrostatic sensors.
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Hemalatha, B., and S. Srinivasan. "Reinforce Coverage Area of Sensor Mote in Wireless Ad-Hoc Networks Using Genetic Algorithm." International Journal of Engineering & Technology 7, no. 3.27 (August 15, 2018): 508. http://dx.doi.org/10.14419/ijet.v7i3.27.18471.
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Wireless sensor based communication is everlasting growing sector within the industry of communication. In WSN improving the life expectancy of the network depends on the energy dissipation of senor devices. Diminishing the energy dissipation of sensor device will enhance the lifetime and device failure which helps in better availability and coverage area of sensor network. One of the dynamic research fields in wireless sensor network is that of coverage. Coverage can be defined as how well each point of interest is monitored by sensor network. In this paper, we investigate the cluster head selection issue, particularly focusing on applications where the upkeep of full network coverage is the fundamental prerequisite. Coverage maintenance for extended period is a pivotal issue in wireless sensor network because of the constrained inbuilt battery in sensors. Coverage maintenance may be prolonged by utilizing the network energy efficiently, by keeping an adequate number of sensors in sensor covers. The clustering algorithm is a solution to reduce energy consumption which can be helpful to the scalability and network lifetime. Assuming serious energy rebalancing with additional clustering algorithm, a Genetic algorithm (GA) based clustering algorithm which evaluates the fitness function by considering the two major parameters distance and energy has been proposed in this paper. Simulation result shows that the proposed solution finds the optimal cluster heads and has prolonged network lifetime and maximum coverage.
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Zang, Yue, Yuyang Peng, Sangdon Park, Han Hai, Fawaz AL-Hazemi, and Mohammad Meraj Mirza. "A Novel Cooperative Transmission Scheme in UAV-Assisted Wireless Sensor Networks." Electronics 11, no. 4 (February 15, 2022): 600. http://dx.doi.org/10.3390/electronics11040600.
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In wireless sensor networks (WSNs), the efficiency of data transmission within a limited time is critical, especially for sensors designed with small batteries. In this paper, we design a cooperative transmission scheme with an energy-charging function in a WSN where an unmanned aerial vehicle (UAV) is considered for sensory data collection and energy charging. Specially, the sensor nodes are powered by the UAV for their data transmission. In the first phase, the UAV transmits the energy signal to the sensor nodes distributed on the ground. All the energy received by the sensor nodes is used to collect and transmit the sensory data to the UAV. In the second phase, local data transmissions are conducted among the collaborating sensor nodes in one cluster. In the third phase, the cooperative nodes send the collected sensory data to the UAV in the form of cooperative transmission. In the proposed scheme, we discovered that the size of the modulation constellation and the assigned time ratio of each phase were the key factors affecting the data transmission efficiency. In order to achieve the maximum data transmission, the optimal modulation constellation size and the optimal time ratio of each phase were found using the Lagrange multiplier method. Numerical results show that the proposed scheme with the optimal constellation size and the optimal time ratio can outperform the existing scheme in terms of the data transmission efficiency.
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Bosse, Stefan, and Uwe Engel. "Augmented Virtual Reality: Combining Crowd Sensing and Social Data Mining with Large-Scale Simulation Using Mobile Agents for Future Smart Cities." Proceedings 4, no. 1 (November 14, 2018): 49. http://dx.doi.org/10.3390/ecsa-5-05762.
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Augmented reality is well known for extending the real world by adding computer-generated perceptual information and overlaid sensory information. In contrast, simulation worlds are commonly closed and rely on artificial sensory information generated by the simulator program or using data collected off-line. In this work, a new simulation paradigm is introduced, providing augmented virtuality by integrating crowd sensing and social data mining in simulation worlds by using mobile agents. The simulation world interacts with real world environments, humans, machines, and other virtual worlds in real-time. Mobile agents are closely related to bots that can interact with humans via chat blogs. Among the mining of physical sensors (temperature, motion, position, light, …), mobile agents can perform Crowd Sensing by participating in question–answer dialogs via a chat blog provided by a WEB App that can be used by the masses. Additionally, mobile agents can act as virtual sensors (offering data exchanged with other agents). Virtual sensors are sensor aggregators performing sensor fusion in a spatially region.
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Bao, Xi Rong, Yue Huang, and Shi Zhang. "A Distributed Motion Algorithm for Mobile Sensor in Hybrid Wireless Sensor Networks." Applied Mechanics and Materials 719-720 (January 2015): 812–17. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.812.
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Constructing a hybrid wireless sensor networks comprising a mix of static sensors and mobile sensors can achieve a balance between improving coverage and reducing the cost of the network. In order to achieve high network coverage, mobile sensor move from a small to a big size of coverage hole in the hybrid wireless sensor networks. Due to the energy of the mobile sensor is limited, how to reduce the moving distance of the mobile sensor and reduce the energy consumption in the process of moving is a very important issue. This paper proposes a distributed minimum cost matching algorithm (DMMA) to redeploy mobile sensor, which can make the level of network coverage to meet the requirement of the environment, while effectively reducing the number of sensors. In our method, static sensors detect coverage hole by Voronoi diagrams, coverage holing sensors and mobile sensors by using DMMA to excellently heal the large coverage holes. Simulation results show that our method can effectively improve the coverage rate of the WSNs, while save the energy of mobile sensors.
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Navone, Christelle, Mathieu Soulier, Isabella Chartier, Julia Simon, Aurelien Oliveira, Claudine Gehin, and Thierry Pauchard. "Flexible Heat Flux Sensor for Firefighters Garment Integration." International Journal of E-Health and Medical Communications 4, no. 1 (January 2013): 36–45. http://dx.doi.org/10.4018/jehmc.2013010104.
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The interest in using optimal equipment to face unknown hazards is growing, as it ultimately save lives. This holds especially true for fire-fighters which are confronted with other hazards during the course of operations. Improvement of their security by an integrated sensory clothing system was the main objective of the European project ProeTEX. In this context, the integration of commercial heat flux sensors into fire-fighters garment has proved the interest of such measurements. However, low flexibility and high cost remain major disadvantages of these sensors. The objective of this work is to develop an innovative heat flux sensor based on a low cost technology. Heat flux sensors have been realized using printable thermoelectric materials and present high sensitivity (146 mV/ (W/cm2)). Their flexibility is compatible with integration in clothes and three specific integrations are proposed and compared. Proof of concept of flexible heat flux sensor is also presented in this paper.
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Liu, Meng-Yang, Cheng-Zhou Hang, Xue-Yan Wu, Li-Yuan Zhu, Xiao-Hong Wen, Yang Wang, Xue-Feng Zhao, and Hong-Liang Lu. "Investigation of stretchable strain sensor based on CNT/AgNW applied in smart wearable devices." Nanotechnology 33, no. 25 (April 1, 2022): 255501. http://dx.doi.org/10.1088/1361-6528/ac5ee6.
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Abstract Stretchable strain sensor, an important paradigm of wearable sensor which can be attached onto clothing or even human skin, is widely used in healthcare, human motion monitoring and human-machine interaction. Pattern-available and facile manufacturing process for strain sensor is pursued all the time. A carbon nanotube (CNT)/silver nanowire (AgNW)-based stretchable strain sensor fabricated by a facile process is reported here. The strain sensor exhibits a considerable Gauge factor of 6.7, long-term durability (>1000 stretching cycles), fast response and recovery (420 ms and 600 ms, respectively), hence the sensor can fulfill the measurement of finger movement. Accordingly, a smart glove comprising a sensor array and a flexible printed circuit board is assembled to detect the bending movement of five fingers simultaneously. Moreover, the glove is wireless and basically fully flexible, it can detect the finger bending of wearer and display the responses distinctly on an APP of a smart phone or a host computer. Our strain senor and smart glove will broaden the materials and applications of wearable sensors.
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Wang, Silin, and Junji Gao. "Overview of Magnetic Field Sensor." Journal of Physics: Conference Series 2613, no. 1 (October 1, 2023): 012012. http://dx.doi.org/10.1088/1742-6596/2613/1/012012.
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Abstract This article summarizes the commonly used in magnetic sensors Hall sensors, Anisotropic magnetoresistive sensor (AMR), Giant magnetoresistance effect sensor (GMR) and Tunneling magnetoresistance sensor (TMR). The structure and working principle of each sensor are introduced. In addition, some error sources of magnetic sensors and the calibration techniques used are introduced, and some typical application examples of each sensor are introduced.
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Ramdhani, Aris, Ahmad Aminudin, and Agus Danawan. "Rancang Bangun Sistem Pengukur Kecepatan Kendaraan Menggunakan Sensor Magnetik." Wahana Fisika 2, no. 1 (June 20, 2017): 28. http://dx.doi.org/10.17509/wafi.v2i1.7021.
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Data kecepatan kendaran di jalan raya sangat berpengaruh bagi keamanan dan keselamatan pengguna jalan raya. Kemajuan tekhnologi sensor sangat membantu dalam mengukur kecepatan kendaraan dengan otomatis. Metode yang umum dipakai ialah metode dengan menggunakan dua buah rangkaian sensor yang sudah diatur pada jarak tertentu. Sensor digunakan sebagai pendeteksi keberadaan kendaraan. Data kecepatan kendaraan didapatkan dengan mencari selang waktu yang dibutuhkan kendaraan melaju dari sensor pertama menuju sensor kedua. Saat kendaraan melaju melewati sensor maka sinyal keluaran sensor menjadi acuan perhitungan waktu start dan stop. Berbagai jenis sensor yang sudah digunakan ialah sensor LDR, sensor ultrasonic, sensor laser, sensor loop induktif dan sensor kamera. Setiap sensor yang sudah dipergunakan memiliki berbagai jenis kekurangan dalam mendeteksi kendaraan pada jalan raya. Oleh karena itu penulis memunculkan ide baru dengan menggunakan sensor magnetik yang memiliki faktor gangguan eksternal yang rendah. Sensor magnetik yang digunakan ialah sensor Giant MagnetoResistance (GMR). Perancangan sistem pengukur kecepatan kendaraan yang penulis lakukan berupa sebuah prototype. Hasil pengujian sistem pengukur kecepatan kendaraan menggunakan sensor magnetik GMR menunjukan respon yang bagus saat pengujian dilakukan pada jarak 30cm dan 70cm antara dua buah sensor GMR.Data speed of vehicles on the highway are very influential to the security and safety of users of the highway. Advances in sensor technology is very helpful in measuring the speed of vehicles with automatic. A common method used is the method by using two sensor circuit which is set at a certain distance. The sensor is used as a detector for the exixtance of the vehicle. Vehicle speed data obtained by finding the time required vehicles drove from the first sensor to the second sensor. When the vehicle drove past the sensor, the sensor output signal to be a reference calculation start and stop time. Many types of sensors that have been used are LDR sensors, ultrasonic sensors, laser sensors, inductive loop sensors and camera sensors. Each of the sensor is already used to have various types of shortcomings in detecting vehicles on highways. Therefore, the authors bring up new ideas by using a magnetic sensor that has a low external noise factor. The type of sensor used magnetic sensor is giant magnetoresistance (GMR). Measuring system design vehicle speed that the author did such a prototype. The results of testing measuring vehicle speed using the GMR sensor showed a good response when testing is done at a distance of 30cm and 70cm between the two GMR sensors.
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Tsai, Rong-Guei, Xiaoyan Lv, Lin Shen, and Pei-Hsuan Tsai. "A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks." Sensors 22, no. 5 (March 4, 2022): 2020. http://dx.doi.org/10.3390/s22052020.
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In wireless sensor networks, it is important to use the right number of sensors to optimize the network and consider the key design and cost. Due to the limited power of sensors, important issues include how to control the state of the sensor through an automatic control algorithm and how to power-save and efficiently distribute work. However, sensor nodes are usually deployed in dangerous or inaccessible locations. Therefore, it is difficult and impractical to supply power to sensors through humans. In this study, we propose a high reliability control algorithm with fast convergence and strong self-organization ability called the sensor activity control algorithm (SACA), which can efficiently control the number of sensors in the active state and extend their use time. In the next round, SACA considers the relationship between the total number of active sensors and the target value and determines the state of the sensor. The data transmission technology of random access is used between the sensor and the base station. Therefore, the sensor in the sleep state does not need to receive the feedback packet from the base station. The sensor can achieve true dormancy and power-saving effects. The experimental results show that SACA has fast convergence, strong self-organization capabilities, and power-saving advantages.
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Kim, Tae-Hyeong, Gi-Hwan Jo, Hyeong-Seok Yun, Kyung-Su Yun, and Tae-Hyoung Park. "Placement Method of Multiple Lidars for Roadside Infrastructure in Urban Environments." Sensors 23, no. 21 (October 29, 2023): 8808. http://dx.doi.org/10.3390/s23218808.
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Sensors on autonomous vehicles have inherent physical constraints. To address these limitations, several studies have been conducted to enhance sensing capabilities by establishing wireless communication between infrastructure and autonomous vehicles. Various sensors are strategically positioned within the road infrastructure, providing essential sensory data to these vehicles. The primary challenge lies in sensor placement, as it necessitates identifying optimal locations that minimize blind spots while maximizing the sensor’s coverage area. Therefore, to solve this problem, a method for positioning multiple sensor systems in road infrastructure is proposed. By introducing a voxel grid, the problem is formulated as an optimization challenge, and a genetic algorithm is employed to find a solution. Experimental findings using lidar sensors are presented to demonstrate the efficacy of this proposed approach.
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Chaudhari, Amit, Rakshith Lokesh, Vuthea Chheang, Sagar M. Doshi, Roghayeh Leila Barmaki, Joshua G. A. Cashaback, and Erik T. Thostenson. "Characterizing the Sensing Response of Carbon Nanocomposite-Based Wearable Sensors on Elbow Joint Using an End Point Robot and Virtual Reality." Sensors 24, no. 15 (July 28, 2024): 4894. http://dx.doi.org/10.3390/s24154894.
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Physical therapy is often essential for complete recovery after injury. However, a significant population of patients fail to adhere to prescribed exercise regimens. Lack of motivation and inconsistent in-person visits to physical therapy are major contributing factors to suboptimal exercise adherence, slowing the recovery process. With the advancement of virtual reality (VR), researchers have developed remote virtual rehabilitation systems with sensors such as inertial measurement units. A functional garment with an integrated wearable sensor can also be used for real-time sensory feedback in VR-based therapeutic exercise and offers affordable remote rehabilitation to patients. Sensors integrated into wearable garments offer the potential for a quantitative range of motion measurements during VR rehabilitation. In this research, we developed and validated a carbon nanocomposite-coated knit fabric-based sensor worn on a compression sleeve that can be integrated with upper-extremity virtual rehabilitation systems. The sensor was created by coating a commercially available weft knitted fabric consisting of polyester, nylon, and elastane fibers. A thin carbon nanotube composite coating applied to the fibers makes the fabric electrically conductive and functions as a piezoresistive sensor. The nanocomposite sensor, which is soft to the touch and breathable, demonstrated high sensitivity to stretching deformations, with an average gauge factor of ~35 in the warp direction of the fabric sensor. Multiple tests are performed with a Kinarm end point robot to validate the sensor for repeatable response with a change in elbow joint angle. A task was also created in a VR environment and replicated by the Kinarm. The wearable sensor can measure the change in elbow angle with more than 90% accuracy while performing these tasks, and the sensor shows a proportional resistance change with varying joint angles while performing different exercises. The potential use of wearable sensors in at-home virtual therapy/exercise was demonstrated using a Meta Quest 2 VR system with a virtual exercise program to show the potential for at-home measurements.
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Yoon, John. "Trustworthiness of Dynamic Moving Sensors for Secure Mobile Edge Computing." Computers 7, no. 4 (November 16, 2018): 63. http://dx.doi.org/10.3390/computers7040063.
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Wireless sensor network is an emerging technology, and the collaboration of wireless sensors becomes one of the active research areas for utilizing sensor data. Various sensors collaborate to recognize the changes of a target environment, to identify, if any radical change occurs. For the accuracy improvement, the calibration of sensors has been discussed, and sensor data analytics are becoming popular in research and development. However, they are not satisfactorily efficient for the situations where sensor devices are dynamically moving, abruptly appearing, or disappearing. If the abrupt appearance of sensors is a zero-day attack, and the disappearance of sensors is an ill-functioning comrade, then sensor data analytics of untrusted sensors will result in an indecisive artifact. The predefined sensor requirements or meta-data-based sensor verification is not adaptive to identify dynamically moving sensors. This paper describes a deep-learning approach to verify the trustworthiness of sensors by considering the sensor data only. The proposed verification on sensors can be done without having to use meta-data about sensors or to request consultation from a cloud server. The contribution of this paper includes (1) quality preservation of sensor data for mining analytics. The sensor data are trained to identify their characteristics of outliers: whether they are attack outliers, or outlier-like abrupt changes in environments; and (2) authenticity verification of dynamically moving sensors, which was possible. Previous unknown sensors are also identified by deep-learning approach.
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Azizi, Shoaib, Ramtin Rabiee, Gireesh Nair, and Thomas Olofsson. "Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices." Energies 14, no. 19 (October 2, 2021): 6296. http://dx.doi.org/10.3390/en14196296.
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The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO2, humidity, and illuminance. The results show that the positions of PIR and CO2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.
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Kim, Se Hoon, Seo Jung Yun, Quoc Khanh Dang, Youngjoon Chee, Sun Gun Chung, Byung-Mo Oh, Keewon Kim, and Han Gil Seo. "Measurement and Correction of Stooped Posture during Gait Using Wearable Sensors in Patients with Parkinsonism: A Preliminary Study." Sensors 21, no. 7 (March 30, 2021): 2379. http://dx.doi.org/10.3390/s21072379.
Full textAbstract:
Stooped posture, which is usually aggravated during walking, is one of the typical postural deformities in patients with parkinsonism. However, the degree of stooped posture is difficult to quantitatively measure during walking. Furthermore, continuous feedback on posture is also difficult to provide. The purpose of this study is to measure the degree of stooped posture during gait and to investigate whether vibration feedback from sensor modules can improve a patient’s posture. Parkinsonian patients with stooped posture were recruited for this study. Two wearable sensors with three-axis accelerometers were attached, one at the upper neck and the other just below the C7 spinous process of the patients. After being calibrated in the most upright posture, the sensors continuously recorded the sagittal angles at 20 Hz and averaged the data at every second during a 6 min walk test. In the control session, the patients walked with the sensors as usual. In the vibration session, sensory feedback was provided through vibrations from the neck sensor module when the sagittal angle exceeded a programmable threshold value. Data were collected and analyzed successfully in a total of 10 patients. The neck flexion and back flexion were slightly aggravated during gait, although the average change was <10° in most patients in both measurement sessions. Therefore, it was difficult to evaluate the effect of sensory feedback through vibration. However, some patients showed immediate response to the feedback and corrected their posture during gait. In conclusion, this preliminary study suggests that stooped posture could be quantitatively measured during gait by using wearable sensors in patients with parkinsonism. Sensory feedback through vibration from sensor modules may help in correcting posture during gait in selected patients.
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Vino, T., S. S. Sivaraju, R. V. V. Krishna, T. Karthikeyan, Yogesh kumar Sharma, K. G. S. Venkatesan, G. Manikandan, R. Selvameena, and Mebratu Markos. "Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy." International Journal of Photoenergy 2022 (October 11, 2022): 1–8. http://dx.doi.org/10.1155/2022/1164613.
Full textAbstract:
A wireless touch network is a distributed, self-organizing network of multiple sensors and actuators in combination with multiple sensors and a radio channel. Also, the security area of such a network can be several meters to several meters. The main difference between wireless sensor networks from traditional computer and telephone networks is the lack of a fixed infrastructure owned by a specific operator or provider. Each user terminal in a touch network is capable of acting as a terminal device only. Despite the long history of sensor networks, the concept of building a sensor network is not finally imposed and expressed in some software and hardware (platform) solutions. In this paper, the design and analysis of multicluster model of the sensor nodes in wireless sensor network with the help of solar energy. This proposed model provides the required energy to transmit the information between two end nodes in different cluster. The communication between the end to end clusters was increased based on this design. The implementation of sensory networks at the current stage depends largely on the specific needs of the industrial problem. The architecture, software, and hardware implementation technology is at an intensive development stage, attracting the attention of developers looking for a technological niche of future makers.
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Honti, Gergely Marcell, and Janos Abonyi. "A Review of Semantic Sensor Technologies in Internet of Things Architectures." Complexity 2019 (June 12, 2019): 1–21. http://dx.doi.org/10.1155/2019/6473160.
Full textAbstract:
Intelligent sensors should be seamlessly, securely, and trustworthy interconnected to enable automated high-level smart applications. Semantic metadata can provide contextual information to support the accessibility of these features, making it easier for machines and humans to process the sensory data and achieve interoperability. The unique overview of sensor ontologies according to the semantic needs of the layers of IoT solutions can serve a guideline of engineers and researchers interested in the development of intelligent sensor-based solutions. The explored trends show that ontologies will play an even more essential role in interlinked IoT systems as interoperability and the generation of controlled linkable data sources should be based on semantically enriched sensory data.
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Naumova, Olga, Vladimir Generalov, Dmitry Shcherbakov, Elza Zaitseva, Yuriy Zhivodkov, Anton Kozhukhov, Alexander Latyshev, et al. "SOI-FET Sensors with Dielectrophoretic Concentration of Viruses and Proteins." Biosensors 12, no. 11 (November 8, 2022): 992. http://dx.doi.org/10.3390/bios12110992.
Full textAbstract:
Quick label-free virus screening and highly sensitive analytical tools/techniques are becoming extremely important in a pandemic. In this study, we developed a biosensing device based on the silicon nanoribbon multichannel and dielectrophoretic controlled sensors functionalized with SARS-CoV-2 spike antibodies for the use as a platform for the detection and studding of properties of viruses and their protein components. Replicatively defective viral particles based on vesicular stomatitis viruses and HIV-1 were used as carrier molecules to deliver the target SARS-CoV-2 spike S-proteins to sensory elements. It was shown that fully CMOS-compatible nanoribbon sensors have the subattomolar sensitivity and dynamic range of 4 orders. Specific interaction between S-proteins and antibodies leads to the accumulation of the negative charge on the sensor surface. Nonspecific interactions of the viral particles lead to the positive charge accumulation. It was shown that dielectrophoretic controlled sensors allow to estimate the effective charge of the single virus at the sensor surface and separate it from the charge associated with the binding of target proteins with the sensor surface.