Utilizing Sensor Arrays to Attain High-Operating Bandwidth

2004 ◽  
Vol 126 (2) ◽  
pp. 294-302
Author(s):  
Sugathevan Suranthiran ◽  
Suhada Jayasuriya
Keyword(s):  
Sensor Array ◽  
Sensor Arrays ◽  
Cost Effective ◽  
Sensor Data ◽  
Pass Band ◽  
Multiple Sensors ◽  
High Bandwidth ◽  
Small Bandwidth ◽  
Operating Bandwidth ◽  
Single Sensor

Proposed in this paper is a methodology for the design of a sensor array of small bandwidth passband sensors (sensors with small bandwidth but different bandwidths) to attain a high operating bandwidth. In certain control applications, it is necessary that a high bandwidth sensor be used for feedback efficiency. The design of a single sensor with the desired high bandwidth may not be easy and economically feasible. A new approach, which recommends the use of an array of small bandwidth pass-band sensors in place of a single sensor of high bandwidth is proposed. It is shown that the idea of sensor arrays can be utilized to obtain a cost effective and efficient solution to the problem posed. The proposed sensor array that consists of multiple sensors with possible overlapping operating regions as defined by their pass-bands requires that an effective fusion technique be used to unite multi-sensor data. A multi-sensor data fusion scheme using Frequency Response Methods is developed to facilitate the possible implementation of proposed sensor arrays.

Implementation of High Bandwidth Sensor Arrays Using Feedback Mechanisms

2004 ◽  
Author(s):  
Sugathevan Suranthiran ◽  
Suhada Jayasuriya
Keyword(s):  
Sensor Arrays ◽  
Cost Effective ◽  
Sensor Data ◽  
Pass Band ◽  
Feedback Mechanisms ◽  
Implementation Scheme ◽  
High Bandwidth ◽  
Operating Bandwidth ◽  
Single Sensor ◽  
Fusion Scheme

Proposed in this paper is a new method to implement the high operating bandwidth sensor arrays. In certain control applications, it is necessary that a high bandwidth sensor be used to improve the efficiency of feedback. The design of a single sensor with the desired high bandwidth may not be easy and economically feasible. It is shown that the idea of sensor arrays can be utilized to obtain a cost effective and efficient solution to the problem posed. It is discussed that an effective data fusion scheme is necessary in order to implement the proposed sensor array that consists of low bandwidth pass-band sensors with possible overlapping operating regions. Moreover, we point out that obtaining accurate sensor models may not be always easy in practice and this may make the proposed sensor arrays inapplicable for certain applications. To address this issue, a new implementation scheme that utilizes feedback mechanisms to combine multi-sensor data is developed. The proposed framework is validated using simulation examples.

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals Collaborative Filtering to Predict Sensor Array Values in Large IoT Networks

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4628
Author(s):  
Fernando Ortega ◽  
Ángel González-Prieto ◽  
Jesús Bobadilla ◽  
Abraham Gutiérrez
Keyword(s):  
Collaborative Filtering ◽  
Failure Rate ◽  
Sensor Array ◽  
Sensor Arrays ◽  
Weather Conditions ◽  
Sensor Data ◽  
Population Movements ◽  
Use Of The Internet ◽  
Rate Threshold

Internet of Things (IoT) projects are increasing in size over time, and some of them are growing to reach the whole world. Sensor arrays are deployed world-wide and their data is sent to the cloud, making use of the Internet. These huge networks can be used to improve the quality of life of the humanity by continuously monitoring many useful indicators, like the health of the users, the air quality or the population movements. Nevertheless, in this scalable context, a percentage of the sensor data readings can fail due to several reasons like sensor reliabilities, network quality of service or extreme weather conditions, among others. Moreover, sensors are not homogeneously replaced and readings from some areas can be more precise than others. In order to address this problem, in this paper we propose to use collaborative filtering techniques to predict missing readings, by making use of the whole set of collected data from the IoT network. State of the art recommender systems methods have been chosen to accomplish this task, and two real sensor array datasets and a synthetic dataset have been used to test this idea. Experiments have been carried out varying the percentage of failed sensors. Results show a good level of prediction accuracy which, as expected, decreases as the failure rate increases. Results also point out a failure rate threshold below which is better to make use of memory-based approaches, and above which is better to choose model-based methods.

scholarly journals Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2180 ◽  
Author(s):  
Prasanna Kolar ◽  
Patrick Benavidez ◽  
Mo Jamshidi
Keyword(s):  
Data Fusion ◽  
Autonomous Navigation ◽  
Current Data ◽  
Obstacle Detection ◽  
Sensor Data ◽  
Depth Cameras ◽  
Multiple Sensors ◽  
Single Sensor ◽  
Sensor Information ◽  
Autonomous Mobility

This paper focuses on data fusion, which is fundamental to one of the most important modules in any autonomous system: perception. Over the past decade, there has been a surge in the usage of smart/autonomous mobility systems. Such systems can be used in various areas of life like safe mobility for the disabled, senior citizens, and so on and are dependent on accurate sensor information in order to function optimally. This information may be from a single sensor or a suite of sensors with the same or different modalities. We review various types of sensors, their data, and the need for fusion of the data with each other to output the best data for the task at hand, which in this case is autonomous navigation. In order to obtain such accurate data, we need to have optimal technology to read the sensor data, process the data, eliminate or at least reduce the noise and then use the data for the required tasks. We present a survey of the current data processing techniques that implement data fusion using different sensors like LiDAR that use light scan technology, stereo/depth cameras, Red Green Blue monocular (RGB) and Time-of-flight (TOF) cameras that use optical technology and review the efficiency of using fused data from multiple sensors rather than a single sensor in autonomous navigation tasks like mapping, obstacle detection, and avoidance or localization. This survey will provide sensor information to researchers who intend to accomplish the task of motion control of a robot and detail the use of LiDAR and cameras to accomplish robot navigation.

Based on D - S Evidence Theory of Solution Concentration Detection Method Research

2014 ◽  
Vol 494-495 ◽  
pp. 869-872
Author(s):  
Xian Bao Wang ◽  
Shi Hai Zhao ◽  
Guo Wei
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Solution Concentration ◽  
Sensor Data ◽  
Fusion Technology ◽  
Feedback Information ◽  
Multiple Sensors ◽  
Multi Sensor Data Fusion ◽  
Single Sensor ◽  
Sensor Information

According to the theory of multi-sensor information fusion technology, based on D - S evidence theory to fuse of multiple sensors feedback information from different angles for detecting solution concentration, and achieving the same judgment; This system uses of D - S evidence theory of multi-sensor data fusion method, not only make up the disadvantages of using a single sensor, but also largely reduce the uncertainty of the judgment. Additionally this system improves the rapidity and accuracy of the solution concentration detection, and broadens the application field of multi-sensor information fusion technology.

A SCENARIO STUDY FOR IMPROVING COST-EFFECTIVENESS IN ACOUSTIC TIME-REVERSAL SOURCE RELOCATION IN AN URBAN ENVIRONMENT

2012 ◽  
Vol 20 (02) ◽  
pp. 1240003 ◽  
Author(s):  
LANBO LIU ◽  
HAO XIE ◽  
DONALD G. ALBERT ◽  
PAUL R. ELLER ◽  
JING-RU C. CHENG
Keyword(s):  
Cost Effectiveness ◽  
Urban Environment ◽  
Time Reversal ◽  
Sensor Array ◽  
Cost Effective ◽  
Urban Setting ◽  
Minimum Number ◽  
Single Sensor ◽  
Processor Unit ◽  
Single Receiver

Through finite difference time domain (FDTD) numerical simulation, we have studied the possible observation settings to improve the cost effectiveness in time-reversal (TR) source relocation in a two-dimensional (2D) urban setting under a number of typical scenarios. All scenario studies were based on the FDTD computation of the acoustic wave field resulted from an impulse source, propagated through an artificial village composed of 15 buildings and a set of sources and receivers, a typical urban setting has been extensively analyzed in previous studies. The FDTD numerical modeling code can be executed on an off-the-shelf graphic processor unit (GPU) that increases the speed of the time-reversal calculations by a factor of 200. With this approach the computational results lead to some significant conclusions. In general, using only one non-line-of-sight (NLOS) single receiver is not enough to do a quality work to re-locate the source via time-reversal. This is particularly true when there are more than one path between the source and this receiver with similar wave energy travel time. However, when the single sensor is located in an acoustic channel, reverberation inside the waveguide may increase the effective aperture of the single receiver enough to give a good location. It is equivalent to say that the waveguide and the single receiver form a "virtual array". It appears that a sensor array with a minimum number of three receivers might be the most cost-effective way to carry out TR source relocation in an urban environment. The most optimal geometry of a sensor array with a minimum number of three receivers could be an equal side-length triangle. Simple analysis showed that by this setup it is possible to catch sound sources from almost all possible azimuths. Effective source relocation essentially depends on the geometry, relativity to the scatters, etc. of the sensing array. Generally, adding another single sensor relatively far away from the main array will not improve the results. It is practically useful and achievable to have a sensor array mounted on the outside of a single building, and in these cases successful source relocations were obtained. As stated by the fundamental TR theory, increasing the number of scatters, here, increasing the number of buildings will definitely be helpful to increase the effectiveness of TR source relocation.

scholarly journals Fusion of Angle Measurements from Hull Mounted and Towed Array Sensors

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 432
Author(s):  
Kausar Jahan ◽  
Koteswara Rao Sanagapallea
Keyword(s):  
Sensor Array ◽  
Sensor Arrays ◽  
Convergence Time ◽  
Fusion Algorithm ◽  
Angle Measurements ◽  
Solution Convergence ◽  
Bearing Angle ◽  
Single Sensor ◽  
Towed Array ◽  
Using Data

Two sensor arrays, hull-mounted array, and towed array sensors are considered for bearings-only tracking. An algorithm is designed to combine the information obtained as bearing (angle) measurements from both sensor arrays to give a better solution. Using data from two different sensor arrays reduces the problem of observability and the observer need not follow the S-maneuver to attain observability of the process. The performance of the fusion algorithm is comparable to that of theoretical Cramer–Rao lower bound and with that of the algorithm when bearing measurements from a single sensor array are considered. Different filters are used for analyzing both algorithms. Monte Carlo runs need to be done to evaluate the performance of algorithms more accurately. Also, the performance of the fusion algorithm is evaluated in terms of solution convergence time.

scholarly journals Weather monitoring and forecasting system using IoT

2021 ◽  
Vol 8 (2) ◽  
pp. 008-016
Author(s):  
Balakrishnan Sivakumar ◽  
Chikkamadaiah Nanjundaswamy
Keyword(s):  
Weather Forecast ◽  
Cost Effective ◽  
Sensor Data ◽  
Solar Panels ◽  
Web Page ◽  
Time Data ◽  
Multiple Sensors ◽  
Wide Range ◽  
Compact Design ◽  
The Web

The system proposed is an advanced solution for weather monitoring that uses IoT to make its real time data easily accessible over a very wide range. The system deals with monitoring weather and climate changes like temperature, humidity, wind speed, moisture, light intensity, UV radiation and even carbon monoxide levels in the air; using multiple sensors. These sensors send the data to the web page and the sensor data is plotted as graphical statistics. The data uploaded to the web page can easily be accessible from anywhere in the world. The data gathered in these web pages can also be used for future references. The project even consists of an app that sends notifications as an effective alert system to warn people about sudden and drastic weather changes. For predicting more complex weather forecast that can’t be done by sensors alone we use an API that analyses the data collected by the sensors and predicts an accurate outcome. This API can be used to access the data anywhere and at any time with relative ease and can also be used to store data for future use. Due to the compact design and fewer moving parts this design requires less maintenance. The components in this project don’t consume much power and can even be powered by solar panels. Compared to other devices that are available in the market the Smart weather monitoring system is cheaper and cost effective. This project can be of great use to meteorological departments, weather stations, aviation and marine industries and even the agricultural industry.

scholarly journals A Novel Multi-Dimensional Composition Method Based on Time Series Similarity for Array Pulse Wave Signals Detecting

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 297
Author(s):  
Hongjie Zou ◽  
Yitao Zhang ◽  
Jun Zhang ◽  
Chuanglu Chen ◽  
Xingguang Geng ◽  
...  
Keyword(s):  
Time Series ◽  
Sensor Array ◽  
Pulse Wave ◽  
Dynamic Pressure ◽  
Sensor Arrays ◽  
Disease Diagnosis ◽  
Micro Electro Mechanical System ◽  
Processing Method ◽  
Multiple Test ◽  
Multiple Sensors

Pulse wave signal sensed over the radial artery on the wrist is a crucial physiological indicator in disease diagnosis. The sensor array composed of multiple sensors has the ability to collect abundant pulse wave information. As a result, it has gradually attracted the attention of practitioners. However, few practical methods are used to obtain a one-dimensional pulse wave from the sensor array’s spatial multi-dimensional signals. The current algorithm using pulse wave with the highest amplitude value as the significant data suffers from low consistency because the signal acquired each time differs significantly due to the sensor’s relative position shift to the test area. This paper proposes a processing method based on time series similarity, which can take full advantage of sensor arrays’ spatial multi-dimensional characteristics and effectively avoid the above factors’ influence. A pulse wave acquisition system (PWAS) containing a micro-electro-mechanical system (MEMS) sensor array is continuously extruded using a stable dynamic pressure input source to simulate the pulse wave acquisition process. Experiments are conducted at multiple test locations with multiple data acquisitions to evaluate the performance of the algorithm. The experimental results show that the newly proposed processing method using time series similarity as the criterion has better consistency and stability.

a-SiN:H Thin Film Diode for Digital Radiography

2000 ◽  
Vol 609 ◽  
Author(s):  
I.A. Popov ◽  
G. Van Doorselaer ◽  
A. Van Calster ◽  
H. De Smet ◽  
J. De Baets ◽  
...  
Keyword(s):  
Thin Film ◽  
Digital Radiography ◽  
Sensor Array ◽  
Schottky Diodes ◽  
Sensor Arrays ◽  
Cost Effective ◽  
X Ray ◽  
Recent Developments ◽  
Overall Performance ◽  
Switching Devices

ABSTRACTRecent developments in the area of cost effective 2D direct x-ray sensor arrays on the base of a-SiN:H back-to-back Schottky diodes and no switching devices per pixel are presented. Discussion focuses on two major aspects: (i) x-ray sensitivity of the sensor itself and possibility of its improvement; (ii) the overall performance of the sensor array.

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