An acoustic sensor technology to detect urine excretion

2022 ◽  
Vol 214 ◽  
pp. 90-106
Author(s):  
Paul R. Shorten ◽  
Brendon G. Welten
Keyword(s):  
Sensor Technology ◽  
Acoustic Sensor ◽  
Urine Excretion

Fiber optic acoustic sensor technology

2005 ◽  
Vol 117 (4) ◽  
pp. 2446-2447 ◽  
Author(s):  
James Cole ◽  
Clay Kirkendall ◽  
Anthony Dandridge
Keyword(s):  
Fiber Optic ◽  
Sensor Technology ◽  
Acoustic Sensor

Application of distribute acoustic sensor technology in oil and gas exploration

2019 ◽  
Author(s):  
Jianhua Huang ◽  
Yanpeng Li ◽  
Xing Liang ◽  
Yuanzhong Chen ◽  
Junjun Wu ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Sensor Technology ◽  
Acoustic Sensor ◽  
Oil And Gas Exploration

scholarly journals Localization in Underwater Acoustic Sensor Networks using Trapezoid

2020 ◽  
Vol 8 (5) ◽  
pp. 186-193
Keyword(s):  
Sensor Networks ◽  
Sensor Technology ◽  
Second Phase ◽  
Acoustic Sensor ◽  
Sink Node ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Linear Trajectory ◽  
Acoustic Sensor Networks ◽  
Source Of Information

Underwater Acoustic Sensor Networks (UASN) has driven a lot of attention from researchers because of advancements in sensor technology and unexplored applications of the ocean. UASNs monitor the targeted area with heterogeneous underwater sensors and relay that information to the onshore sink node in mission-critical applications. It is very much essential to know the source of information whenever some critical events happened in the UASNs. Hence, to learn the source of information, i.e. finding the location of the sensor node is crucial. To address this issue, in this paper, initially geometrical object such as trapezoid is used to form the clusters in the targeted region. After that, the proposed localization algorithm is applied and it works in three phases. (i) In the first phase, the sink node initiates the trapezoid formation process through Trapezoid Formation Agent (TFA) and divides the whole network into trapezoids of different geometrical shapes by traveling across the linear trajectory and also creates a search data structure. (ii) In the second phase, the sink deploys AUV at a certain depth for patrolling along the linear trajectory and broadcasts real-time location contained beacon messages at specified points through that anchor nodes are localized by using RSSI. (iii) Sink node activates Localization Agent (LA) in the third phase to perform the location identification process at the trapezoids by using the trilateration method. This work addresses the inherent localization issue of UASNs algorithms and hence it applies to the applications which consider the localization issue. This proposed scheme is well supported by node agencies and knowledgebase. The proposed scheme is simulated in C and validated by different performance parameters.

scholarly journals Advances in Electromagnetic Piezoelectric Acoustic Sensor Technology for Biosensor-Based Detection

Chemosensors ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 58
Author(s):  
Gábor Mészáros ◽  
Sanaz Akbarzadeh ◽  
Brian De La Franier ◽  
Zsófia Keresztes ◽  
Michael Thompson
Keyword(s):  
Sensor Technology ◽  
Shear Mode ◽  
Biological Macromolecules ◽  
Analytical Sensitivity ◽  
Acoustic Sensor ◽  
Sensing Applications ◽  
Sensor Device ◽  
Acoustic Quality ◽  
Quartz Disc ◽  
Thickness Shear

The ultra-high frequency EMPAS (electromagnetic piezoelectric acoustic sensor) device is composed of an electrode-less quartz disc in which shear oscillation is induced by an AC-powered magnetic coil located 30 μm below the substrate. This configuration allows the instigation of high acoustic harmonics (in the region of 49th–53rd), with the resulting enhanced analytical sensitivity for biosensor purposes compared to the conventional thickness-shear mode device. In this paper, we introduce significant improvements to the operation of the system with respect to sensing applications. This includes a new interface program and the capability to measure the acoustic quality factor not available in the prototype version. The enhanced configuration is subject to testing through biosensor detection of surface adsorption of biological macromolecules, which include β-casein, and a gelsolin-actin complex.

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