Journal articles on the topic 'Multi-sensors integration'
To see the other types of publications on this topic, follow the link: Multi-sensors integration.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Multi-sensors integration.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
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.
Full textAbstract:
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.
2
Giampetruzzi, Lucia, Amilcare Barca, Flavio Casino, Simonetta Capone, Tiziano Verri, Pietro Siciliano, and Luca Francioso. "Multi-Sensors Integration in a Human Gut-On-Chip Platform." Proceedings 2, no. 13 (November 13, 2018): 1022. http://dx.doi.org/10.3390/proceedings2131022.
Full textAbstract:
In the conventional culture systems in vitro, the challenging organoid approach have recently been overcome by the development of microfluidic Organ Chip models of human intestine. The potential future applications of Intestine-on-Chips in disease modelling, drug development and personalized medicine are leading research to identify and investigate limitations of modern chip-based systems and to focus the attention on the gut epithelium and its specific barrier function playing a significant role in many human disorders and diseases. In this paper, we propose and discuss the importance to implement a multi-parameter analysis on an engineered platform for developing an Epithelial Gut On Chip model.
3
An, Boxing, Ying Ma, Wenbo Li, Meng Su, Fengyu Li, and Yanlin Song. "Three-dimensional multi-recognition flexible wearable sensor via graphene aerogel printing." Chemical Communications 52, no. 73 (2016): 10948–51. http://dx.doi.org/10.1039/c6cc05910d.
Full text
4
Wei, Liang, Yongcheng Li, Zhimei Cui, Baoshi Wang, Guanlang Huang, Zhiming Wang, and Jie Wei. "Research and Demonstration of Intelligent Multi-Physical Quantity Integration Sensor for Transmission Lines." Journal of Physics: Conference Series 2215, no. 1 (February 1, 2022): 012021. http://dx.doi.org/10.1088/1742-6596/2215/1/012021.
Full textAbstract:
Abstract The digital grid requires sensors to be widely deployed, safe, and reliable. At present, the single functional sensors suffered from redundant sensing system, repeated construction and low utilization rate. Therefore, this paper researched the multi-physical quantity integration sensor for a quad-bundle spacer on 500kV transmission lines. The sensor was composed of self-supplying rings and the monitoring host. Based on the non-contact current measurement technology, energy supply technology, intelligent sensing technology, low power consumption technology, reliability design technology, and other advanced technologies, this paper designed the hardware, software, and protective structure of the sensor, which can monitor the current and temperature of bubbles, channel side image and infrared image on transmission lines, ambient temperature, humidity, and air pressure. Finally, the multi-physical quantity integration sensors have been used on transmission lines in China Southern Power Grid, and the functions were verified. The sensors promote the automation, information, and digitization of monitoring transmission lines.
5
Papadimitriou, Costas, and Evaggelos Ntotsios. "Optimization Algorithms for System Integration." Advances in Science and Technology 56 (September 2008): 514–23. http://dx.doi.org/10.4028/www.scientific.net/ast.56.514.
Full textAbstract:
This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising in structural dynamics and related to (1) model parameter estimation used for finite element model updating, (2) model-based damage detection in structures and (3) optimal sensor location for parameter estimation and damage detection. These problems are formulated as single- and multi-objective optimization problems of continuous or discrete-valued variables. Gradient-based, evolutionary, hybrid and heuristic algorithms are presented that effectively address issues related to the estimation of multiple local/global solutions and computational complexity arising in single and multi-objective optimization involving continuous and discrete variables.
6
Retscher, Günther. "Test and Integration of Location Sensors for a Multi-sensor Personal Navigator." Journal of Navigation 60, no. 1 (December 15, 2006): 107–17. http://dx.doi.org/10.1017/s037346330700402x.
Full textAbstract:
In the work package “Integrated Positioning” of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environments) we are dealing with the navigation and guidance of visitors to our University. The start points are the public transport stops in the surroundings of the Vienna University of Technology and the system users should be guided to certain office rooms or persons. For the user's position determination different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors, such as a digital compass and gyro for heading determination, accelerometers for the determination of the distance travelled, a barometric pressure sensor for altitude determination and, for indoor areas, location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter. An optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the senors in the stochastic filter model, the sensor characteristics and performance were investigated in several tests. The tests were performed in different environments either with free satellite visibility, in urban canyons or inside buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach are presented in the paper.
7
Ebel, P., S. Saha, and X. X. Zhu. "FUSING MULTI-MODAL DATA FOR SUPERVISED CHANGE DETECTION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 243–49. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-243-2021.
Full textAbstract:
Abstract. With the rapid development of remote sensing technology in the last decade, different modalities of remote sensing data recorded via a variety of sensors are now easily accessible. Different sensors often provide complementary information and thus a more detailed and accurate Earth observation is possible by integrating their joint information. While change detection methods have been traditionally proposed for homogeneous data, combining multi-sensor multi-temporal data with different characteristics and resolution may provide a more robust interpretation of spatio-temporal evolution. However, integration of multi-temporal information from disparate sensory sources is challenging. Moreover, research in this direction is often hindered by a lack of available multi-modal data sets. To resolve these current shortcomings we curate a novel data set for multi-modal change detection. We further propose a novel Siamese architecture for fusion of SAR and optical observations for multi-modal change detection, which underlines the value of our newly gathered data. An experimental validation on the aforementioned data set demonstrates the potentials of the proposed model, which outperforms common mono-modal methods compared against.
8
Liu, Shijie, Zhaoyou Ma, Xinming Guo, Xucai Zhuang, Yonghong Chen, Jianqing Wu, and Jianping Xing. "Research and development of intelligent safety sensor integration devices for autonomous driving." Journal of Physics: Conference Series 2196, no. 1 (February 1, 2022): 012002. http://dx.doi.org/10.1088/1742-6596/2196/1/012002.
Full textAbstract:
Abstract Grasping the status of vehicles timely and accurately is the key to avoid traffic accidents and collecting data from multi-sensors is significant for development of road-side intelligent sensor technology. In this paper, LiDAR (Light Detection and Ranging) and camera sensors are tested, and the sensor data can be processed and analyzed, and the display can be integrated. In this paper, a multi-sensor data acquisition integration device based on Raspberry Pi is proposed, which can realize the optimal processing of data and simultaneous acquisition display function. This method avoids the tedium of using an IPC and improves the efficiency of data acquisition and sensor integration.
9
Lai, Tao, Guang Long Wang, Wen Jie Zhu, and Feng Qi Gao. "Attitude Determination by Integration of Multi-Sensors Based on Federated Kalman Filter." Applied Mechanics and Materials 602-605 (August 2014): 2958–61. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2958.
Full textAbstract:
Micro inertial measurement unit integration storage test system is a typical multi-sensor information fusion system consists of microsensors. The Federated Kalman filter is applied to micro inertial measurement unit integration storage test system. The general structure and characteristics of Federated Kalman filter is expounded. The four-order Runge-Kutta method based on quaternion differential equation was used to dispose the output angular rate data from gyroscope, and the recurrence expressions was established too. The control system based ARM Cortex-M4 master-slave structure is adopted in this paper. The result shown that the dimensionality reduced algorithm significantly reduces implementation complexity of the method and the amount computation. The filtering effect and real-time performance have much increased than traditionally method.
10
Wu, Hongsheng, and Junwang Hu. "Artificial Intelligence Platform Construction and Integration Based on Multi-sensor Fusion." MATEC Web of Conferences 359 (2022): 01028. http://dx.doi.org/10.1051/matecconf/202235901028.
Full textAbstract:
Sensor is an important source of data transmission, through the integration of mechanical radar, inertial measurement unit and other sensors, building an artificial intelligence platform, will effectively save data information. By taking advantage of sensor fusion, the data of gyroscope and accelerometer are transferred to the background, and then the time stamp of artificial intelligence platform is aligned to get useful and usable information. By combining the mechanical radar and millimeter wave radar, an artificial intelligence platform is built, which makes full use of the synergetic advantage of the related sensors, captures the data information independently and saves it according to the time stamp. This paper focuses on the construction and integration of artificial intelligence platform based on multi-sensor fusion.
11
Schrank, Franz. "Sensor Integration Technologies for Internet of Things." International Symposium on Microelectronics 2015, S1 (October 1, 2015): S1—S34. http://dx.doi.org/10.4071/isom-2015-slide-3.
Full textAbstract:
Internet of things (IoT) will influence all areas from consumer to health care to building and home automation and to observation. IoT enables direct communication between objects via internet. The main functional blocks of IoT devices are sensing, data transmitting, processing and analysis and subsequent actuation. As a result such a system will consist of sensors, actuators, wireless connection, data processing, power management, energy harvesting, memory and software. A total market volume of almost 400 Bio US$ is predicted for 2024 whereof about 12Bio US$ are expected for IoT sensors (Yole2014)). The main challenges are to reduce footprint (e.g. wearables, swarm), reduce costs of system, improve reliability and provide better performance. For example the costs of today's smart sensor systems are in the 100–1000US$ range and for 2024 an ASP in the 1US$ $ level is expected (Yole2014). To enable this, a high level of integration is needed for the next generations of IoT sensors. This will on one hand reduce costs and form factor but also enable multi sensors devices. More than Moore integration of functions offers the potential to meet both performance and cost targets for mass-market adoption. In addition to SoC (System on Chip) and SiP (System in Package) heterogeneous 3D integrations will be key enablers. 3D integration with the main technology bricks like TSV (Through Silicon Via), RDL (Redistribution Layer), D2W (Die to Wafer) and W2W (Wafer to Wafer) stacking and embedding allows to combine different technologies - different CMOS notes, MEMS, photonics, etc. At the same time expensive single die packaging can be avoided. The presentation will focus on reviewing 3D integration technologies and their potential for IoT from the perspective of a sensor solution provider.
12
GAO, ZHIYUAN, SUYING YAO, JIANGTAO XU, and CHAO XU. "DYNAMIC RANGE EXTENSION OF CMOS IMAGE SENSORS USING MULTI-INTEGRATION TECHNIQUE WITH COMPACT READOUT." Journal of Circuits, Systems and Computers 22, no. 06 (July 2013): 1350042. http://dx.doi.org/10.1142/s0218126613500424.
Full textAbstract:
A multi-integration technology with compact readout method to extend CMOS image sensor's dynamic range is presented. Compared with the timing of rolling readout, compact readout extends the available pixel readout time by adjusting the time-domain offset between two adjacent rows and each integration time in one frame. Thus the column readout bus is working continuously rather than intermittently, which makes good use of the whole integration time and the available readout time can be extended. This dynamic range extension technology was implemented on a prototype chip with a 128 × 128 pixel array. The pixel readout time with compact readout method is almost as 3 times long as the one with rolling readout method while 39 dB dynamic range extension is achieved at 120 fps.
13
Rajkumar, Dr S., Aklilu Teklemariam, and Addisalem Mekonnen. "Hybrid Multi-Sensor Integration for Static or Dynamic Obstacle Detection, Tracking and Classification for Autonomous Vehicle." Journal of University of Shanghai for Science and Technology 23, no. 06 (June 22, 2021): 1288–93. http://dx.doi.org/10.51201/jusst/21/06424.
Full textAbstract:
Autonomous Vehicles (AV) reduces human intervention by perceiving the vehicle’s location with respect to the environment. In this regard, utilization of multiple sensors corresponding to various features of environment perception yields not only detection but also enables tracking and classification of the object leading to high security and reliability. Therefore, we propose to deploy hybrid multi-sensors such as Radar, LiDAR, and camera sensors. However, the data acquired with these hybrid sensors overlaps with the wide viewing angles of the individual sensors, and hence convolutional neural network and Kalman Filter (KF) based data fusion framework was implemented with a goal to facilitate a robust object detection system to avoid collisions inroads. The complete system tested over 1000 road scenarios for real-time environment perception showed that our hardware and software configurations outperformed numerous other conventional systems. Hence, this system could potentially find its application in object detection, tracking, and classification in a real-time environment.
14
Huang, Jing, Hai Hua Li, Rui Yang, and Hai Yan Chen. "A Clustering Based Data Integration Algorithm in Wireless Sensor Networks." Advanced Materials Research 186 (January 2011): 552–55. http://dx.doi.org/10.4028/www.scientific.net/amr.186.552.
Full textAbstract:
Data fusion is an important research issue in wireless sensor networks (WSN). The clustering based approach can reduce the interference among nodes, maintain the balance of energy consumption within WSNs, and therefore prolong the lifetime of WSNs. A clustering-based algorithm called LEACH-EC is presented in the paper. Aiming at solving the problems of the existing algorithms, the LEACH-EC takes the static clustering approach to reduce the energy consumption during clustering stage by first clustering sensors and then selecting the heads of respective clusters. When the heads of clusters send data to the base station, a proposed multi-hop strategy is adopted to further decrease the energy consumption of head sensors. Compared with the existing algorithms, the LEACH-EC has shown a good performance on both extending the lifetime of WSNs as well as reducing energy consumption of sensors.
15
Mastichiadis, C., A. E. Niotis, P. S. Petrou, S. E. Kakabakos, and K. Misiakos. "Capillary-based immunoassays, immunosensors and DNA sensors – steps towards integration and multi-analysis." TrAC Trends in Analytical Chemistry 27, no. 9 (October 2008): 771–84. http://dx.doi.org/10.1016/j.trac.2008.08.003.
Full text
16
Abd, Moaed A., Rudy Paul, Aparna Aravelli, Ou Bai, Leonel Lagos, Maohua Lin, and Erik D. Engeberg. "Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition." Sensors 21, no. 13 (June 24, 2021): 4324. http://dx.doi.org/10.3390/s21134324.
Full textAbstract:
Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands.
17
Mishra, B., and J. Susaki. "Optical and SAR data integration for automatic change pattern detection." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-7 (September 19, 2014): 39–46. http://dx.doi.org/10.5194/isprsannals-ii-7-39-2014.
Full textAbstract:
Automatic change pattern mapping in urban and sub-urban area is important but challenging due to the diversity of urban land use pattern. With multi-sensor imagery, it is possible to generate multidimensional unique information of Earth surface features that allow developing a relationship between a response of each feature to synthetic aperture radar (SAR) and optical sensors to track the change automatically. Thus, a SAR and optical data integration framework for change detection and a relationship for automatic change pattern detection were developed. It was carried out in three steps: (i) Computation of indicators from SAR and optical images, namely: normalized difference ratio (NDR) from multi-temporal SAR images and the normalized difference vegetation index difference (NDVI) from multi-temporal optical images, (ii) computing the change magnitude image from NDR and ΔNDVI and delineating the change area and (iii) the development of an empirical relationship, for automatic change pattern detection. The experiment was carried out in an outskirts part of Ho Chi Minh City, one of the fastest growing cities in the world. The empirical relationship between the response of surface feature to optical and SAR imagery has successfully delineated six changed classes in a very complex urban sprawl area that was otherwise impossible with multi-spectral imagery. The improvement of the change detection results by making use of the unique information on both sensors, optical and SAR, is also noticeable with a visual inspection and the kappa index was increased by 0.13 (0.75 to 0.88) in comparison to only optical images.
18
Mao, Yi, Yi Yang, and Yuxin Hu. "Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm." Sensors 19, no. 22 (November 15, 2019): 4975. http://dx.doi.org/10.3390/s19224975.
Full textAbstract:
Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration.
19
Zeng, Xu, Hai-Tao Deng, Dan-Liang Wen, Yao-Yao Li, Li Xu, and Xiao-Sheng Zhang. "Wearable Multi-Functional Sensing Technology for Healthcare Smart Detection." Micromachines 13, no. 2 (February 2, 2022): 254. http://dx.doi.org/10.3390/mi13020254.
Full textAbstract:
In recent years, considerable research efforts have been devoted to the development of wearable multi-functional sensing technology to fulfill the requirements of healthcare smart detection, and much progress has been achieved. Due to the appealing characteristics of flexibility, stretchability and long-term stability, the sensors have been used in a wide range of applications, such as respiration monitoring, pulse wave detection, gait pattern analysis, etc. Wearable sensors based on single mechanisms are usually capable of sensing only one physiological or motion signal. In order to measure, record and analyze comprehensive physical conditions, it is indispensable to explore the wearable sensors based on hybrid mechanisms and realize the integration of multiple smart functions. Herein, we have summarized various working mechanisms (resistive, capacitive, triboelectric, piezoelectric, thermo-electric, pyroelectric) and hybrid mechanisms that are incorporated into wearable sensors. More importantly, to make wearable sensors work persistently, it is meaningful to combine flexible power units and wearable sensors and form a self-powered system. This article also emphasizes the utility of self-powered wearable sensors from the perspective of mechanisms, and gives applications. Furthermore, we discuss the emerging materials and structures that are applied to achieve high sensitivity. In the end, we present perspectives on the outlooks of wearable multi-functional sensing technology.
20
Huang, Yunbao, Haiyan Li, Qifu Wang, and Liping Chen. "Integrating multiple sensors for the closed-loop three-dimensional digitization." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 226, no. 11 (February 1, 2012): 2816–34. http://dx.doi.org/10.1177/0954406212436442.
Full textAbstract:
In this article, we present a set of novel techniques, which include (1) sensor-stage calibration, (2) high-level script programming for the flexible control of data sensing, and (3) a framework for dynamic data sensing, visualization and shape modeling. It enables the integration of multiple three-dimensional sensors into one controlled three-dimensional digitization system for the closed-loop of data sensing and shape modeling. In this system, point, line, and area sensors with different sensing coverage, accuracies, and resolutions can be integrated into a multi-stage platform on which data acquisition from each sensor can be programmed in a controlled manner. In this manner, the closed-loop of data sensing and shape modeling can be achieved, which can significantly improve the overall digitization efficiency and shape modeling quality. Finally, two three-dimensional digitization examples of such multi-sensor system are demonstrated, (1) complementary integration of multiple sensors for three-dimensional digitization and (2) the closed-loop of dynamic data sensing and shape modeling to significantly improve overall sensing efficiency and shape modeling quality.
21
Amemiya, Yoshiteru, and Shin Yokoyama. "Characteristics of stacked multi-slot ring resonator sensors." Sensor Review 37, no. 3 (June 19, 2017): 357–63. http://dx.doi.org/10.1108/sr-11-2016-0243.
Full textAbstract:
Purpose This paper aims to develop ring resonator type optical sensors for high-sensitive detection of biomaterials and a solution concentration surrounding sensor devices. The sensing characteristics of a proposed device are investigated. Design/methodology/approach The proposed device structure is multi-slot ring resonator where the horizontal slots are arranged in vertical direction called as stacked multi-slot ring resonator. The ring resonator consists of silicon nitride because of several advantages such as easy integration of Si photo-detectors. A high sensitivity is expected in this structure because the slot height is precisely controlled by the thickness of stacked silicon nitride and etched silicon oxide layers. Sensing characteristics are evaluated from the simulated effective refractive index using the finite element method and sucrose solution sensing is confirmed using polydimethylsiloxane fluid channel. Findings In the simulation for the solution concentration sensor, the detection sensitivity is enhanced with increasing the slot height and the number of slots. On the other hand, for the biomaterial sensor such as the adsorbed antigen-antibody reaction, the sensitivity increases with decreasing the slot height. In this case, more than four times higher sensitivity is expected compared with the slot ring resonator sensor with vertical single slot and 0.1-0.2 μm slot width. Originality/value This paper presents an improved new structure of ring resonator type sensors and its optimum design parameters. The sensing characteristics are evaluated, and, for the biomaterial sensor, the sensitivity is high in comparison to the previous slot ring resonator.
22
Šaliga, Ján, Ondrej Kováč, and Imrich Andráš. "Analog-to-Information Conversion with Random Interval Integration." Sensors 21, no. 10 (May 19, 2021): 3543. http://dx.doi.org/10.3390/s21103543.
Full textAbstract:
A novel method of analog-to-information conversion—the random interval integration—is proposed and studied in this paper. This method is intended primarily for compressed sensing of aperiodic or quasiperiodic signals acquired by commonly used sensors such as ECG, environmental, and other sensors, the output of which can be modeled by multi-harmonic signals. The main idea of the method is based on input signal integration by a randomly resettable integrator before the AD conversion. The integrator’s reset is controlled by a random sequence generator. The signal reconstruction employs a commonly used algorithm based on the minimalization of a distance norm between the original measurement vector and vector calculated from the reconstructed signal. The signal reconstruction is performed by solving an overdetermined problem, which is considered a state-of-the-art approach. The notable advantage of random interval integration is simple hardware implementation with commonly used components. The performance of the proposed method was evaluated using ECG signals from the MIT-BIH database, multi-sine, and own database of environmental test signals. The proposed method performance is compared to commonly used analog-to-information conversion methods: random sampling, random demodulation, and random modulation pre-integration. A comparison of the mentioned methods is performed by simulation in LabVIEW software. The achieved results suggest that the random interval integration outperforms other single-channel architectures. In certain situations, it can reach the performance of a much-more complex, but commonly used random modulation pre-integrator.
23
Van Blaricum, Vicki L., and Vincent F. Hock. "Water Distribution System Modeling and Remote Monitoring." Advanced Materials Research 38 (March 2008): 132–42. http://dx.doi.org/10.4028/www.scientific.net/amr.38.132.
Full textAbstract:
Localized internal corrosion of water distribution piping is difficult to detect, diagnose, and mitigate. This paper describes the demonstration and validation of multi-parameter water quality sensors and corrosion rate sensors that were permanently installed at a U. S. Army installation to detect corrosion problems and fine-tune the chemical treatment program. This paper will include results of the sensor demonstration and validation. Follow-on work includes the integration of the sensors with a dynamic real-time water distribution system chemical and hydraulic simulation. This work will also be described.
24
Yang, Nan, Zhen Feng Shao, and Lei Zhang. "Mobile Vehicle-Borne Environmental Monitoring Based on Environmental Multi-Sensor Integration." Applied Mechanics and Materials 522-524 (February 2014): 38–43. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.38.
Full textAbstract:
Environmental monitoring is increasingly playing a significant role in such aspects as environment protection, emergency disaster response and rescue, and macro decision-making etc. However, the intrinsic characteristics of complexity and spatial-temporal diversity, multi-scale features and heterogeneity brought from various means of data acquisition make the integration of multi-source data with high-efficiency becomes an international challenge nowadays. In this paper, the design and implementation of a vehicle-borne platform based on Internet of Things for environmental monitoring has been achieved. And then, by merging and matching environmental data and spatial data, more intensive multi-source environmental parameters and information can be obtained to act as meaningful supplementation of fixed environmental monitoring stations. The research of this paper is conductive to the transition of environmental monitoring from static methods to dynamic methods and from a small amount of data-based empirical model to sensor network-based quantitative model. Mobile environmental monitoring platform integrating with multiple sensors that can make environmental monitoring more timely, dynamic, integrated and intelligent will be the beneficial attempt and the development trend.
25
Masuda, Ryosuke, and Motoji Takahashi. "Measurement of Object Movement in Robot Hand by Sensor Integration of Multi-Tactile Sensors." Journal of Robotics and Mechatronics 5, no. 1 (February 20, 1993): 38–45. http://dx.doi.org/10.20965/jrm.1993.p0038.
Full text
26
., Nurul Shahida Sulaiman. "GENERATING THREE-DIMENSIONAL PHOTO-REALISTIC MODEL OF ARCHAEOLOGICAL MONUMENT VIA MULTI-SENSORS’ DATA INTEGRATION." International Journal of Research in Engineering and Technology 02, no. 10 (October 25, 2013): 362–73. http://dx.doi.org/10.15623/ijret.2013.0210055.
Full text
27
Leopold, Mathias, Thomas Hoffmann, Klemens Opfermann, Enrico Pannicke, Georg Rose, and Elmar Woschke. "Concept of a multi sensor and freely configurable patient table for CT applications." Current Directions in Biomedical Engineering 4, no. 1 (September 1, 2018): 501–4. http://dx.doi.org/10.1515/cdbme-2018-0120.
Full textAbstract:
AbstractConventional computed tomography (CT) systems are encapsulated in hardware and software. Integration of further imaging modalities and sensors which can acquire prior knowledge for dose saving image acquisition and reconstruction techniques are barely possible. Within the scope of our research project, an open interface and freely configurable CT system is now being developed. The integration of further modalities and sensors into this system is a main target. A subproject deals with a multi sensor patient table, which provides additional information through integrated sensors. In particular, force sensors are installed inside the patient table to determine the patient’s mass. This value can be used to specify the required tube voltage, so that a more precise setting can be made in comparison to today‘s clinical practice. Studys show that a more precise kVp estimation can significantly reduce patient dose. Sensors for the monitoring of respiration and pulse are also integrated into the setup of the patient table. On the one hand, these are designed to encourage the patients to minimize disturbing movements and on the other hand to generate trigger signals for the examination. In addition to the sensor concept of the table, a position control system for vertical and horizontal movement of the table is integrated. The position of the table can be adjusted using different input devices so that a fast and intuitive handling of the table movement can be achieved for standard diagnostic and CT guided interventional procedures. The communication between all sensors, actors and the CT ist realized via the Robot Operating System (ROS) framework.
28
Guo, De Feng, Bin Liu, Xiao Tian Jin, and Hong Jian Liu. "Human Activity Recognition Using Smart-Phone Sensors." Applied Mechanics and Materials 571-572 (June 2014): 1019–29. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.1019.
Full textAbstract:
Activity recognition is a challenging problem for context-aware systems and applications. Many studies in this field has mainly adopted techniques based on supervised or semi-supervised learning algorithms to recognize activities by movement patterns gathered through sensors, but these existing systems suffer from complex issues for feature representations of sensor data and multi-sensors integration. In this paper, we propose a novel feature learning method for activity recognition based on entropy and construct an activity recognition model with multi-class AdaBoost algorithm. Experiments on sensor data from a real dataset demonstrate the significant potential of our method to extract features for activity recognition. The experimental results also show recognition model based on multi-class AdaBoost is effective. The average precision and recall for six activities are 95.9% and 95.9%, respectively, which are higher than results obtained by using other methods such as Support Vector Machine (SVM) or K-Nearest Neighbor (KNN).
29
Duan, Jing Xuan, and Han Sen Wang. "Research on Big Data Consistency Algorithm of Multi-Sensor Fusion." Applied Mechanics and Materials 721 (December 2014): 291–94. http://dx.doi.org/10.4028/www.scientific.net/amm.721.291.
Full textAbstract:
For the situation of data inconsistency and error irregular in multi-sensor detection, this paper based on the traditional measure of consistency, introduced Mahalanobis distance measurement to achieve approximate evaluation of data consistency between two sensors; then combined with the nature of membership function in the fuzzy theory to define support functions which measure the local measurement information and utilization efficiency, thereby obtaining assessments to sensor detection with better observations reliability, higher reliability. Simulation results show that, the weighted reliability to the measurement of multi-sensor observation data consistency can significantly improve the robustness of consistency measure, can eliminate the influence of sensor performance due to instability, effectively identify the sensor with unstable performance and remove it, providing data integration with sensors in consistency.
30
Chávez, José Luis, Alfonso F. Torres-Rua, Wayne E. Woldt, Huihui Zhang, Christopher C. Robertson, Gary W. Marek, Dong Wang, Derek M. Heeren, Saleh Taghvaeian, and Christopher M. U. Neale. "A Decade of Unmanned Aerial Systems in Irrigated Agriculture in the Western U.S." Applied Engineering in Agriculture 36, no. 4 (2020): 423–36. http://dx.doi.org/10.13031/aea.13941.
Full textAbstract:
Highlights Unmanned aerial systems (UAS) are able to provide data for precision irrigation management. Improvements are needed regarding UAS platforms, sensors, processing software, and regulations. Integration of multi-scale imagery into scientific irrigation scheduling tools are needed for technology adoption. Abstract . Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible to use sUAS technology to produce maps of actual crop coefficients, actual crop evapotranspiration, and soil water deficits, for irrigation management, the technology and regulations need to evolve further to facilitate a successful wide adoption and application. Improvements and standards are needed in terms of cameras’ spectral (bands) ranges, radiometric resolutions and associated calibrations, fuel/power technology for longer missions, better imagery processing software, and easier FAA approval of higher altitudes flight missions among other issues. Furthermore, the sUAS technology would play a larger role in irrigated agriculture when integrating multi-scale data (sUAS, ground-based or proximal, satellite) and soil water sensors is addressed, including the need for advances on processing large amounts of data from multiple and different sources, and integration into scientific irrigation scheduling (SIS) systems for convenience of decision making. Desirable technological innovations, and features of the next generation of UAS platforms, sensors, software, and methods for irrigated agriculture, are discussed. Keywords: Agricultural water management, Irrigation prescription mapping, Irrigation scheduling, Precision irrigation, Remote sensing, Sensors, Spatial crop evaOotranspiration, Unmanned aerial systems.
31
Zhao, Boxin, Xiaolong Chen, Xiaolin Zhao, Jun Jiang, and Jiahua Wei. "Real-Time UAV Autonomous Localization Based on Smartphone Sensors." Sensors 18, no. 12 (November 27, 2018): 4161. http://dx.doi.org/10.3390/s18124161.
Full textAbstract:
Localization in GPS-denied environments has become a bottleneck problem for small unmanned aerial vehicles (UAVs). Smartphones equipped with multi-sensors and multi-core processors provide a choice advantage for small UAVs for their high integration and light weight. However, the built-in phone sensor has low accuracy and the phone storage and computing resources are limited, which make the traditional localization methods unable to be readily converted to smartphone-based ones. The paper aims at exploring the feasibility of the phone sensors, and presenting a real-time, less memory autonomous localization method based on the phone sensors, so that the combination of “small UAV+smartphone” can operate in GPS-denied areas regardless of the overload problem. Indoor and outdoor flight experiments are carried out, respectively, based on an off-the-shelf smartphone and a XAircraft 650 quad-rotor platform. The results show that the precision performance of the phone sensors and real-time accurate localization in indoor environment is possible.
32
Lorenz, Sandra, Peter Seidel, Pedram Ghamisi, Robert Zimmermann, Laura Tusa, Mahdi Khodadadzadeh, I. Cecilia Contreras, and Richard Gloaguen. "Multi-Sensor Spectral Imaging of Geological Samples: A Data Fusion Approach Using Spatio-Spectral Feature Extraction." Sensors 19, no. 12 (June 21, 2019): 2787. http://dx.doi.org/10.3390/s19122787.
Full textAbstract:
Rapid, efficient and reproducible drillcore logging is fundamental in mineral exploration. Drillcore mapping has evolved rapidly in the recent decade, especially with the advances in hyperspectral spectral imaging. A wide range of imaging sensors is now available, providing rapidly increasing spectral as well as spatial resolution and coverage. However, the fusion of data acquired with multiple sensors is challenging and usually not conducted operationally. We propose an innovative solution based on the recent developments made in machine learning to integrate such multi-sensor datasets. Image feature extraction using orthogonal total variation component analysis enables a strong reduction in dimensionality and memory size of each input dataset, while maintaining the majority of its spatial and spectral information. This is in particular advantageous for sensors with very high spatial and/or spectral resolution, which are otherwise difficult to jointly process due to their large data memory requirements during classification. The extracted features are not only bound to absorption features but recognize specific and relevant spatial or spectral patterns. We exemplify the workflow with data acquired with five commercially available hyperspectral sensors and a pair of RGB cameras. The robust and efficient spectral-spatial procedure is evaluated on a representative set of geological samples. We validate the process with independent and detailed mineralogical and spectral data. The suggested workflow provides a versatile solution for the integration of multi-source hyperspectral data in a diversity of geological applications. In this study, we show a straight-forward integration of visible/near-infrared (VNIR), short-wave infrared (SWIR) and long-wave infrared (LWIR) data for sensors with highly different spatial and spectral resolution that greatly improves drillcore mapping.
33
Murtiyoso, Arnadi, Pierre Grussenmeyer, Deni Suwardhi, and Rabby Awalludin. "Multi-Scale and Multi-Sensor 3D Documentation of Heritage Complexes in Urban Areas." ISPRS International Journal of Geo-Information 7, no. 12 (December 17, 2018): 483. http://dx.doi.org/10.3390/ijgi7120483.
Full textAbstract:
The 3D documentation of heritage complexes or quarters often requires more than one scale due to its extended area. While the documentation of individual buildings requires a technique with finer resolution, that of the complex itself may not need the same degree of detail. This has led to the use of a multi-scale approach in such situations, which in itself implies the integration of multi-sensor techniques. The challenges and constraints of the multi-sensor approach are further added when working in urban areas, as some sensors may be suitable only for certain conditions. This paper describes the integration of heterogeneous sensors as a logical solution in addressing this problem. The royal palace complex of Kasepuhan Cirebon, Indonesia, was taken as a case study. The site dates to the 13th Century and has survived to this day as a cultural heritage site, preserving within itself a prime example of vernacular Cirebonese architecture. This type of architecture is influenced by the tropical climate, with distinct features designed to adapt to the hot and humid year-long weather. In terms of 3D documentation, this presents specific challenges that need to be addressed both during the acquisition and processing stages. Terrestrial laser scanners, DSLR cameras, as well as UAVs were utilized to record the site. The implemented workflow, some geometrical analysis of the results, as well as some derivative products will be discussed in this paper. Results have shown that although the proposed multi-scale and multi-sensor workflow has been successfully employed, it needs to be adapted and the related challenges addressed in a particular manner.
34
Malik, Muhammad Hassan, Andreas Tsiamis, Hubert Zangl, Alfred Binder, Srinjoy Mitra, and Ali Roshanghias. "Die-Level Thinning for Flip-Chip Integration on Flexible Substrates." Electronics 11, no. 6 (March 8, 2022): 849. http://dx.doi.org/10.3390/electronics11060849.
Full textAbstract:
Die-level thinning, handling, and integration of singulated dies from multi-project wafers (MPW) are often used in research, early-stage development, and prototyping of flexible devices. There is a high demand for thin silicon devices for several applications, such as flexible electronics. To address this demand, we study a novel post-processing method on two silicon devices, an electrochemical impedance sensor, and Complementary Metal Oxide Semiconductor (CMOS) die. Both are drawn from an MPW batch, thinned at die-level after dicing and singulation down to 60 µm. The thinned dies were flip-chip bonded to flexible substrates and hermetically sealed by two techniques: thermosonic bonding of Au stud bumps and anisotropic conductive paste (ACP) bonding. The performance of the thinned dies was assessed via functional tests and compared to the original dies. Furthermore, the long-term reliability of the flip-chip bonded thinned sensors was demonstrated to be higher than the conventional wire-bonded sensors.
35
Zhao, Li, Xiao, Meng, Han, and Yu. "Sensor Drift Compensation Based on the Improved LSTM and SVM Multi-Class Ensemble Learning Models." Sensors 19, no. 18 (September 5, 2019): 3844. http://dx.doi.org/10.3390/s19183844.
Full textAbstract:
Drift is an important issue that impairs the reliability of sensors, especially in gas sensors. The conventional method usually adopts the reference gas to compensate for the drift. However, its classification accuracy is not high. We propose a supervised learning algorithm that is based on multi-classifier integration for drift compensation in this paper, which incorporates drift compensation into the classification process, motivated by the fact that the goal of drift compensation is to improve the classification performance. In our method, with the obtained characteristics of sensors and the advantage of Support Vector Machine (SVM) in few-shot classification, the improved Long Shot Term Memory (LSTM) is integrated to build the multi-class classifier model. We tested the proposed approach on the publicly available time series dataset that was collected over three years by the metal-oxide gas sensors. The results clearly indicate the superiority of multiple classifier approach, which achieves higher classification accuracy as compared with different approaches during testing period with an ensemble of classifiers in the presence of sensor drift over time.
36
Song, Qingwu, Fengjiang, Chunpeng Li, Yifan Wang, Zhengjun Bao, and Shanrui Shao. "Multi-parameter infrared sensing method for operation state of power equipment." Journal of Physics: Conference Series 2451, no. 1 (March 1, 2023): 012005. http://dx.doi.org/10.1088/1742-6596/2451/1/012005.
Full textAbstract:
Abstract Aiming at the problems of difficult extraction and reconstruction of multi-parameter signals and poor perception effect of power equipment operation status, a multi-parameter infrared perception method of power equipment operation status is proposed. The multi-parameter (sound, light, electricity, vibration, heat, and environment) sensors of power equipment operation status are selected, the multi-parameter sensor integration framework is built based on the Internet of things technology, the multi-parameter sensors are effectively integrated, the power equipment operation status parameter signals are collected and reconstructed, the power equipment operation status perception model is built, the unsupervised classification and AR algorithm are introduced, and the reconstructed signals are fitted, to realize the infrared perception of power equipment operation status. The experimental data show that the integrity of power equipment operation state parameters and the accuracy of power equipment operation state perception obtained by the proposed method are higher, which proves that the proposed method has a good effect on power equipment operation state perception.
37
Pensieri, Sara, Dionisis Patiris, Stylianos Alexakis, Marios N. Anagnostou, Aristides Prospathopoulos, Christos Tsabaris, and Roberto Bozzano. "Integration of Underwater Radioactivity and Acoustic Sensors into an Open Sea Near Real-Time Multi-Parametric Observation System." Sensors 18, no. 8 (August 20, 2018): 2737. http://dx.doi.org/10.3390/s18082737.
Full textAbstract:
This work deals with the installation of two smart in-situ sensors (for underwater radioactivity and underwater sound monitoring) on the Western 1-Mediterranean Moored Multisensor Array (W1-M3A) ocean observing system that is equipped with all appropriate modules for continuous, long-term and real-time operation. All necessary tasks for their integration are described such as, the upgrade of the sensors for interoperable and power-efficient operation, the conversion of data in homogeneous and standard format, the automated pre-process of the raw data, the real-time integration of data and metadata (related to data processing and calibration procedure) into the controller of the observing system, the test and debugging of the developed algorithms in the laboratory, and the obtained quality-controlled data. The integration allowed the transmission of the acquired data in near-real time along with a complete set of typical ocean and atmospheric parameters. Preliminary analysis of the data is presented, providing qualitative information during rainfall periods, and combine gamma-ray detection rates with passive acoustic data. The analysis exhibits a satisfactory identification of rainfall events by both sensors according to the estimates obtained by the rain gauge operating on the observatory and the remote observations collected by meteorological radars.
38
Rekatsinas, Christoforos S., and Dimitris A. Saravanos. "A time domain spectral layerwise finite element for wave structural health monitoring in composite strips with physically modeled active piezoelectric actuators and sensors." Journal of Intelligent Material Systems and Structures 28, no. 4 (July 28, 2016): 488–506. http://dx.doi.org/10.1177/1045389x16649700.
Full textAbstract:
A new explicit, two-dimensional plane strain, time domain spectral finite element is developed to enhance the simulation of guided waves generated by active piezoelectric sensors in laminated composite strips. A new multi-field layerwise theory is formulated for composite laminates with piezoelectric actuators and sensors which captures straight-crested symmetric and anti-symmetric Lamb waves. Third-order Hermite polynomial splines are employed for the approximation of displacements and electric potential through the thickness, and the piezoelectric actuators and sensors are physically modeled through coupled electromechanical governing equations. A multi-node finite element formulation is presented entailing displacement and electric degrees of freedom at nodes collocated with Gauss–Lobatto–Legendre integration points. Stiffness, diagonal mass, piezoelectric, and electric permittivity matrices are described, and the coupled transient electromechanical response is predicted by a properly formulated explicit time integration scheme. The numerical results of a nine-node time domain spectral finite element are correlated with the reported numerical results and with measured Lamb wave data generated by piezoceramic active sensor pairs in carbon/epoxy plate strips. Important effects introduced by the stiffness and mass of the active actuator/sensor system on Lamb wave propagation are captured by the developed finite element and quantified.
39
Cannon, M. E., R. Nayak, G. Lachapelle, O. S. Salychev, and V. V. Voronov. "Low-Cost INS/GPS Integration: Concepts and Testing." Journal of Navigation 54, no. 1 (January 2001): 119–34. http://dx.doi.org/10.1017/s0373463300001259.
Full textAbstract:
The high cost of inertial units is the main obstacle for their inclusion in precision navigation systems to support a variety of application areas. Standard inertial navigation systems (INS) use precise gyro and accelerometer sensors; however, newer inertial devices with compact, lower precision sensors have become available in recent years. This group of instruments, called motion sensors, is six to eight times less costly than a standard INS. Given their weak stand-alone accuracy and poor run-to-run stability, such devices are not usable as sole navigation systems. Even the integration of a motion sensor into a navigation system as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of using a motion sensor, specifically the MotionPak™, integrated with DGPS and DGLONASS information, to provide accurate position and attitude information, and to assess its capability to bridge satellite outages for up to 20 seconds. The motion sensor has three orthogonally mounted ‘solid-state’ micro- machined quartz angular rate sensors, and three high performance linear servo accelerometers mounted in a compact, rugged package. Advanced algorithms are used to integrate the GPS and motion sensor data. These include INS error damping, calculated platform corrections using DGPS (or DGPS/DGLONASS) output, velocity correction, attitude correction and error model estimation for prediction. This multi-loop algorithm structure is very robust, which guarantees a high level of software reliability. Vehicular and aircraft test trials were conducted with the system in land vehicle mode and the results are discussed. Simulated outages in GPS availability were made to assess the bridging accuracy of the system. Results show that a bridging accuracy of up to 3 m after 10 seconds in vehicular mode and a corresponding accuracy of 6 m after 20 seconds in aircraft mode can be obtained, depending on vehicle dynamics and the specific MotionPak™ unit used. The attitude accuracy was on the order of 22 to 25 arcmin for roll and pitch, and about 44 arcmin for heading.
40
Gräbner, Daniel, Simon Dödtmann, Gerrit Dumstorff, and Frieder Lucklum. "3-D-printed smart screw: functionalization during additive fabrication." Journal of Sensors and Sensor Systems 7, no. 1 (March 20, 2018): 143–51. http://dx.doi.org/10.5194/jsss-7-143-2018.
Full textAbstract:
Abstract. Integrating sensors into machine parts is a necessary step for the development of smart or intelligent components. Sensors integrated into materials such as concrete, fiber compounds, or metals are already used to measure strain, temperature, or corrosion. The integration is mostly done during fabrication, where the sensor is recast in the material during processing. However, approaches to integrate sensors into parts fabricated by additive manufacturing are still rarely found. Especially in the case of rapid prototyping, additive techniques are already substituting the machining of parts using classical technologies like cutting, drilling and milling. To characterize such 3-D-printed machine parts the direct integration of sensing elements is the next logical step. This can be done in multi-material printing by using insulating, magnetic, and conductive materials. In the case of single material printing, our idea is to integrate a sensing element during the printing process itself. As proof-of-concept, we present the functionalization of 3-D-printed screws. Strain gauges screen-printed on a 6 µm thick foil are interposed into the 3-D part during microstereolithography printing. We measure the torsional strain in the screw head to calculate the prestressing force in screws made from different plastic materials. We also analyze the defect effect by comparing it to screws without integrated elements.
41
Länge, Kerstin. "Bulk and Surface Acoustic Wave Sensor Arrays for Multi-Analyte Detection: A Review." Sensors 19, no. 24 (December 6, 2019): 5382. http://dx.doi.org/10.3390/s19245382.
Full textAbstract:
Bulk acoustic wave (BAW) and surface acoustic wave (SAW) sensor devices have successfully been used in a wide variety of gas sensing, liquid sensing, and biosensing applications. Devices include BAW sensors using thickness shear modes and SAW sensors using Rayleigh waves or horizontally polarized shear waves (HPSWs). Analyte specificity and selectivity of the sensors are determined by the sensor coatings. If a group of analytes is to be detected or if only selective coatings (i.e., coatings responding to more than one analyte) are available, the use of multi-sensor arrays is advantageous, as the evaluation of the resulting signal patterns allows qualitative and quantitative characterization of the sample. Virtual sensor arrays utilize only one sensor but combine it with enhanced signal evaluation methods or preceding sample separation, which results in similar results as obtained with multi-sensor arrays. Both array types have shown to be promising with regard to system integration and low costs. This review discusses principles and design considerations for acoustic multi-sensor and virtual sensor arrays and outlines the use of these arrays in multi-analyte detection applications, focusing mainly on developments of the past decade.
42
Joslyn, Cliff A., Lauren Charles, Chris DePerno, Nicholas Gould, Kathleen Nowak, Brenda Praggastis, Emilie Purvine, Michael Robinson, Jennifer Strules, and Paul Whitney. "A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information." Sensors 20, no. 12 (June 17, 2020): 3418. http://dx.doi.org/10.3390/s20123418.
Full textAbstract:
Integration of multiple, heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations from different sensor types in a meaningful and efficient way to track multiple targets. Because different sensors have differing error models, we seek a theoretically justified quantification of the agreement among ensembles of sensors, both overall for a sensor collection, and also at a fine-grained level specifying pairwise and multi-way interactions among sensors. We demonstrate that the theory of mathematical sheaves provides a unified answer to this need, supporting both quantitative and qualitative data. Furthermore, the theory provides algorithms to globalize data across the network of deployed sensors, and to diagnose issues when the data do not globalize cleanly. We demonstrate and illustrate the utility of sheaf-based tracking models based on experimental data of a wild population of black bears in Asheville, North Carolina. A measurement model involving four sensors deployed among the bears and the team of scientists charged with tracking their location is deployed. This provides a sheaf-based integration model which is small enough to fully interpret, but of sufficient complexity to demonstrate the sheaf’s ability to recover a holistic picture of the locations and behaviors of both individual bears and the bear-human tracking system. A statistical approach was developed in parallel for comparison, a dynamic linear model which was estimated using a Kalman filter. This approach also recovered bear and human locations and sensor accuracies. When the observations are normalized into a common coordinate system, the structure of the dynamic linear observation model recapitulates the structure of the sheaf model, demonstrating the canonicity of the sheaf-based approach. However, when the observations are not so normalized, the sheaf model still remains valid.
43
Smith, J. A., D. Jevtics, B. Guilhabert, M. D. Dawson, and M. J. Strain. "Hybrid integration of chipscale photonic devices using accurate transfer printing methods." Applied Physics Reviews 9, no. 4 (December 2022): 041317. http://dx.doi.org/10.1063/5.0121567.
Full textAbstract:
Transfer printing is becoming widely adopted as a back-end process for the hybrid integration of photonic and electronic devices. Integration of membrane components, with micrometer-scale footprints and sub-micron waveguide dimensions, imposes strict performance requirements on the process. In this review, we present an overview of transfer printing for integrated photonics applications, covering materials and fabrication process considerations, methods for efficient optical coupling, and high-accuracy inter-layer alignment. We present state-of-the-art integration demonstrations covering optical sources and detectors, quantum emitters, sensors, and opto-mechanical devices. Finally, we look toward future developments in the technology that will be required for dense multi-materials integration at wafer scales.
44
Xu, Fenlan, Xiuyan Li, Yue Shi, Luhai Li, Wei Wang, Liang He, and Ruping Liu. "Recent Developments for Flexible Pressure Sensors: A Review." Micromachines 9, no. 11 (November 7, 2018): 580. http://dx.doi.org/10.3390/mi9110580.
Full textAbstract:
Flexible pressure sensors are attracting great interest from researchers and are widely applied in various new electronic equipment because of their distinct characteristics with high flexibility, high sensitivity, and light weight; examples include electronic skin (E-skin) and wearable flexible sensing devices. This review summarizes the research progress of flexible pressure sensors, including three kinds of transduction mechanisms and their respective research developments, and applications in the fields of E-skin and wearable devices. Furthermore, the challenges and development trends of E-skin and wearable flexible sensors are also briefly discussed. Challenges of developing high extensibility, high sensitivity, and flexible multi-function equipment still exist at present. Exploring new sensing mechanisms, seeking new functional materials, and developing novel integration technology of flexible devices will be the key directions in the sensors field in future.
45
Okuyama, Eiki, Kohei Konda, and Hiromi Ishikawa. "Surface Profile Measurement Based on the Concept of Multi-Step Division of Length." International Journal of Automation Technology 11, no. 5 (August 30, 2017): 716–20. http://dx.doi.org/10.20965/ijat.2017.p0716.
Full textAbstract:
Many error separation techniques to separate a surface profile from the parasitic motion of the instrument using multiple sensors and/or multiple scans have been proposed. In recent years, large-scale surface profile measurements have become required. When a measured surface profile is large, the number of sampling points becomes large. As the result, the influence of random error becomes large. Previously, a multi-step technique for the division of length was used to decide the short scale from the large scale. An important requirement of this multi-step technique for the division of length is to keep high accuracy at several key points. We applied this technique to the integration method for surface profile measurement and proposed a combination of the large-scale integration method and the short-scale integration method. The results of the theoretical analysis, simulation, and experiment show that this combination method decreases the influence of random error propagation for surface profile measurement.
46
Zhu, Yu, and Xiao. "An Unconventional Multiple Low-Cost IMU and GPS-Integrated Kinematic Positioning and Navigation Method Based on Singer Model." Sensors 19, no. 19 (October 2, 2019): 4274. http://dx.doi.org/10.3390/s19194274.
Full textAbstract:
To release the strong dependence of the conventional inertial navigation mechanization on the a priori low-cost inertial measurement unit (IMU) error model, this research applies an unconventional multi-sensor integration strategy to integrate multiple low-cost IMUs and a global positioning system (GPS) for mass-market automotive applications. The unconventional integration strategy utilizes a basic three-dimensional (3D) kinematic trajectory model as the system model to directly estimate navigational parameters, and it allows the measurements from all of the sensors independently participating in measurement updates. However, the less complex kinematic model cannot realize smooth transitions between different motion statuses for the road vehicle with acceleration maneuvers. In this manuscript, we establish a more practical 3D kinematic trajectory model based on a “current” statistical Singer acceleration model to realize smooth transitions for the maneuvering vehicle. In addition, taking advantage of the unconventional strategy, we individually model the systematic errors of each IMU and the measurements of all sensors, in contrast to most existing approaches that adopt the common-mode errors for different sensors of the same design. A real dataset involving a GPS and multiple IMUs is processed to validate the success of the proposed algorithm model under the unconventional integration strategy.
47
FABRE, S., A. APPRIOU, and X. BRIOTTET. "SENSOR FUSION INTEGRATING CONTEXTUAL INFORMATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 09, no. 03 (June 2001): 369–409. http://dx.doi.org/10.1142/s0218488501000855.
Full textAbstract:
The application of multi-sensor fusion, which aims at recogizing a state among a set of hypotheses for object classification, is of major interest as regards the performance improvement brought by the sensor complementarily. Nevertheless this needs to take into account the more accurate as possible information and take advantage of the statistical learning of the previous measurements acquired by sensors. The classical probabilistic fusion methods lack of performance when the previous learning is not representative of the real measurements provided by sensors. The theory of evidence is then introduced to face this disadvantage by integrating a further information which is the context of the sensor acquisitions. In this paper, we propose a formalism of modeling of the sensor reliability to the context that leads to two methods of integration when all the hypotheses, associated to the objects of the scene acquired by sensors, are previously learnt: the first one amounts to integrate this further information in the fusion rule as degrees of trust and the second models the sensor reliability directly as mass functions. These two methods are based on the theory of fuzzy events. Afterwards, we are interested in the evolvement of these two methods in the case where the previous learning is unavailable for a hypothesis associated to an object of the scene and compare these two methods in order to deduce a global method of contextual information integration in the fusion process.
48
Yang, Yuan, Yongjiang Huang, Haoran Yang, Tingting Zhang, Zixuan Wang, and Xixiang Liu. "Real-Time Terrain-Following of an Autonomous Quadrotor by Multi-Sensor Fusion and Control." Applied Sciences 11, no. 3 (January 25, 2021): 1065. http://dx.doi.org/10.3390/app11031065.
Full textAbstract:
For the application of the autonomous guidance of a quadrotor from confined undulant ground, terrain-following is the major issue for flying at a low altitude. This study has modified the open-source autopilot based on the integration of a multi-sensor receiver (a Global Navigation Satellite System (GNSS)), a Lidar-lite (a laser-range-finder device), a barometer and a low-cost inertial navigation system (INS)). These automatically control the position, attitude and height (a constant clearance above the ground) to allow terrain-following and avoid obstacles based on multi-sensors that maintain a constant height above flat ground or with obstacles. The INS/Lidar-lite integration is applied for the attitude and the height stabilization, respectively. The height control is made by the combination of an extended Kalman filter (EKF) estimator and a cascade proportional-integral-derivative (PID) controller that is designed appropriately for the noise characteristics of low accuracy sensors. The proposed terrain-following is tested by both simulations and real-world experiments. The results indicate that the quadrotor can continuously navigate and avoid obstacles at a real-time response of reliable height control with the adjustment time of the cascade PID controller improving over 50% than that of the PID controller.
49
Müller, Alexander, Hannah Haneke, Valerie Kirchberger, Giulio Mastella, Michael Dommasch, Uta Merle, Oliver Heinze, et al. "Integration of mobile sensors in a telemedicine hospital system: remote-monitoring in COVID-19 patients." Journal of Public Health 30, no. 1 (October 15, 2021): 93–97. http://dx.doi.org/10.1007/s10389-021-01655-2.
Full textAbstract:
Abstract Aim The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability. Subject and methods Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work. Results Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system’s integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine. Conclusion Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique.
50
Bakuła, K., A. Lejzerowicz, M. Pilarska-Mazurek, W. Ostrowski, J. Górka, P. Biernat, P. Czernic, et al. "SENSOR INTEGRATION AND APPLICATION OF LOW-SIZED MOBILE MAPPING PLATFORM EQUIPPED WITH LIDAR, GPR AND PHOTOGRAMMETRIC SENSORS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2022 (May 30, 2022): 167–72. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2022-167-2022.
Full textAbstract:
Abstract. The article aims to analyse the possibilities of GPR, LiDAR, and photogrammetric sensors integration in a specific application, considering the various combination of sensor and their parameters. This text also discusses the possibility of using LiDAR sensors in a low-sized mobile platform for the inventory of the road lane in a dense urban area. The text presents the opportunities and recommendations of GPR and LiDAR sensors for their selection and the possibility of using them. In the case of LiDAR and photogrammetric data, two planned applications were indicated: platform georeferencing and mapping. The accuracy and noise of the Livox Avia LiDAR sensor and point cloud obtained from the Sony A7R camera with image-matching were analysed for a surface inventory. Despite the sufficient density and detail of the data, the intensity distinguishing different surfaces, the noise of LiDAR data at the level of 2 cm was too high to do the inventory of minor damages and analyse road surfaces. Higher accuracy was achieved at the level of 1 cm for photogrammetric point clouds. The article also presents the concept of integrating multi-source data visualised into the form of an oriented point cloud showing both what is above and below the earth's surface, which enables the synergy effect and joint analysis of data with entirely different characteristics.