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.

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.

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.

Optimal Scheduling and Filtering of Distorted Multi-Sensor Data

2002 ◽  
Author(s):  
Sugathevan Suranthiran ◽  
Suhada Jayasuriya
Keyword(s):  
Error Function ◽  
Sensor Data ◽  
Practical Implementation ◽  
Signal Recovery ◽  
Fusion Procedure ◽  
Source Data ◽  
True Representation ◽  
Single Sensor ◽  
Fusion Scheme ◽  
Recovery Schemes

In this paper, a framework to schedule and filter distorted multi-sensor outputs is developed. The distortion caused by sensor nonlinearity is considered. As the distorted signal is not a true representation of the original signal, it is often necessary to develop and incorporate signal recovery schemes. Once such a scheme is developed, implementation may be straightforward if the system is employed with a single sensor. When the bandwidth of a signal of interest is very high, the use of a single sensor may not be feasible. High cost and accuracy are major concerns worth noting. It is proposed that a good practical solution to this problem is to employ an array of low bandwidth sensors. Practical Implementation of recovery schemes is very challenging and difficult in this case due to a possible overlapping of multi-source data. This sensor scheduling problem is investigated in detail and a data fusion scheme based on the optimization of weighted error function is initiated and developed for the two-sensor case. Simulation results are presented to validate the fusion procedure developed.

A practical approach on non-regular sampling and universal demosaicing of raw image sensor data

2020 ◽  
Vol 2020 (1) ◽  
pp. 91-95
Author(s):  
Philipp Backes ◽  
Jan Fröhlich
Keyword(s):  
Image Quality ◽  
Source Code ◽  
Image Sensor ◽  
Sensor Data ◽  
Color Filter ◽  
Lowpass Filter ◽  
Sampling Errors ◽  
Regular Sampling ◽  
Single Sensor ◽  
Similar Image Quality

Non-regular sampling is a well-known method to avoid aliasing in digital images. However, the vast majority of single sensor cameras use regular organized color filter arrays (CFAs), that require an optical-lowpass filter (OLPF) and sophisticated demosaicing algorithms to suppress sampling errors. In this paper a variety of non-regular sampling patterns are evaluated, and a new universal demosaicing algorithm based on the frequency selective reconstruction is presented. By simulating such sensors it is shown that images acquired with non-regular CFAs and no OLPF can lead to a similar image quality compared to their filtered and regular sampled counterparts. The MATLAB source code and results are available at: http://github. com/PhilippBackes/dFSR

scholarly journals Trace Detection of Pentaerythritol Tetranitrate Using Electrochemical Gas Sensors

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Praveen K. Sekhar ◽  
Jie Zhou ◽  
Hui Wang ◽  
Eric R. Hamblin
Keyword(s):  
Gas Sensors ◽  
Cost Effective ◽  
Pentaerythritol Tetranitrate ◽  
Screening System ◽  
Trace Detection ◽  
False Negatives ◽  
Quantitative Measurements ◽  
Front End ◽  
Effective Manner ◽  
Single Sensor

Selective and sensitive detection of trace amounts of pentaerythritol tetranitrate (PETN) is demonstrated. The screening system is based on a sampling/concentrator front end and electrochemical potentiometric gas sensor as the detector. A single sensor is operated in the dominant hydrocarbon (HC) and nitrogen oxides (NOx) mode by varying the sensor operating condition. The potentiometric sensor with integrated heaters was used to capture the signature of PETN. Quantitative measurements based on hydrocarbon and nitrogen oxide sensor responses indicated that the detector sensitivity scaled proportionally with the mass of the explosives (10 μg down to 200 ng). The ratio of the HC integrated peak area to the NOxintegrated peak area is identified as an indicator of selectivity. The HC/NOxratio is unique for PETN and has a range from 1.7 to 2.7. This detection technique has the potential to become an orthogonal technique to the existing explosive screening technologies for reducing the number of false positives/false negatives in a cost-effective manner.

scholarly journals Health Monitoring and Diagnosis of Equipment Based on Multi-sensor Fusion

2018 ◽  
Vol 14 (04) ◽  
pp. 4
Author(s):  
Xuemei Yao ◽  
Shaobo Li ◽  
Yong Yao ◽  
Xiaoting Xie
Keyword(s):  
Evidence Theory ◽  
Sensor Data ◽  
Uncertain Information ◽  
Fusion Algorithm ◽  
Monitoring And Diagnosis ◽  
Multi Sensor Data Fusion ◽  
Basic Probability ◽  
Optimal Fusion ◽  
Single Sensor ◽  
Mechanical Devices

As the information measured by a single sensor cannot reflect the real situation of mechanical devices completely, a multi-sensor data fusion based on evidence theory is introduced. Evidence theory has the advantage of dealing with uncertain information. However, it produces unreasonable conclusions when the evidence conflicts. An improved fusion method is proposed to solve this problem. Basic probability assignment of evidence is corrected according to evidence and sensor weights, and an optimal fusion algorithm is selected by comparing an introduced threshold and a conflict factor. The effectiveness and practicability of the algorithm are tested by simulating the monitoring and diagnosis of rolling bearings. The result shows that the method has better robustness.

A Friction Stir Welding Platform of Thin Plates

2012 ◽  
Vol 628 ◽  
pp. 206-210 ◽  
Author(s):  
Jia Liang Zhang ◽  
Bei Zhi Li ◽  
Xin Chao Zhang ◽  
Qing Xia Wang
Keyword(s):  
Friction Stir Welding ◽  
Virtual Instrument ◽  
Production Efficiency ◽  
Cost Effective ◽  
Field Analysis ◽  
Sensor Data ◽  
Thin Plates ◽  
Increase Production Efficiency ◽  
Friction Stir ◽  
Welding Processes

Friction stir welding processes involve many variables. Engineers and operators often find it difficult to effectively design or control it. The objective of this work is to develop a friction stir welding platform of thin plates to improve welding quality and to increase production efficiency. The study is conducted by using finite element modeling and temperature field analysis technology to obtain optimization parameters, and using virtual instrument, multi-sensor data fusion to monitor the force of the stirring spindle. Experiment results show that the developed platform can reach the requirements of processing quality and is cost-effective.

scholarly journals An Introduction to 5G Network Slicing Technology

Telecom IT ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 21-29
Author(s):  
B. Goldstein ◽  
V. Elagin ◽  
K. Kobzev ◽  
A. Grebenshchikova
Keyword(s):  
Service Providers ◽  
Smart Cities ◽  
Effective Means ◽  
Cost Effective ◽  
Network Slicing ◽  
Radio Access ◽  
5G Network ◽  
High Bandwidth ◽  
Shared Infrastructure ◽  
Levels Of Service

Communications Service Providers are looking to 5G technology as an enabler for new revenues, with network slicing providing a cost-effective means of supporting multiple services on shared infrastructure. Different radio access technologies, network architectures, and core functions can be brought together under software control to deliver appropriate Quality of Service “slices,” enabling new levels of service innovation, such as high bandwidth for video applications, low latency for automation, and mass connectivity for Smart Cities.

scholarly journals Sensing as a Service for the Internet of Things

2016 ◽  
Vol 4 (3) ◽  
pp. 28
Author(s):  
Omar Subhi Aldabbas
Keyword(s):  
Internet Of Things ◽  
Cost Effective ◽  
Sensor Data ◽  
Detection Accuracy ◽  
Heterogeneous Services ◽  
Coordination Languages ◽  
Spatio Temporal ◽  
Temporal Events ◽  
New Applications ◽  
Common Application

Internet of Things (IoT) is a ubiquitous embedded ecosystem known for its capability to perform common application functions through coordinating resources, which are distributed on-object or on-network domains. As new applications evolve, the challenge is in the analysis and usage of multimodal data streamed by diverse kinds of sensors. This paper presents a new service-centric approach for data collection and retrieval. This approach considers objects as highly decentralized, composite and cost effective services. Such services can be constructed from objects located within close geographical proximity to retrieve spatio-temporal events from the gathered sensor data. To achieve this, we advocate Coordination languages and models to fuse multimodal, heterogeneous services through interfacing with every service to achieve the network objective according to the data they gather and analyze. In this paper we give an application scenario that illustrates the implementation of the coordination models to provision successful collaboration among IoT objects to retrieve information. The proposed solution reduced the communication delay before service composition by up to 43% and improved the target detection accuracy by up to 70%, while maintaining energy consumption 20% lower than its best rivals in the literature.

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