Wireless Sensing of Physical Parameters Inside Hermetically Enclosed Conductive Envelopes

2007 ◽  
Author(s):  
Martin Kluge ◽  
Jordi Sabater ◽  
Josef Schalk ◽  
Luong V. Ngo ◽  
Helmut Seidel ◽  
...  
Keyword(s):  
Electromagnetic Waves ◽  
Wireless Sensors ◽  
High Reliability ◽  
Aerospace Industry ◽  
Wireless Sensor ◽  
Physical Parameters ◽  
Wireless Sensing ◽  
Fuel Tanks ◽  
Radio Transmitters ◽  
High Level

In the modern aeronautics and aerospace industry, there is a manifold amount of applications emerging for wireless sensors. While many new systems are making use of radio transmitters, EADS Innovation Works has developed a concept for transmitting energy and data to the inside of hermetically sealed envelopes used for hydraulic accumulators, fuel tanks, oxygen bottles, etc. For such kind of metal enclosures, the use of radio frequency is impossible as the electromagnetic waves are blocked by the surrounding material. Classical approaches like using wire-based feed-throughs threaten the reliability of the overall system and hence, they are less attractive especially when safety relevant components are targeted. The system described in this paper makes use of ultrasonic transmission techniques in order to power and communicate with a wireless sensor inside a metal enclosure. An innovative platform and communication concept allows to efficiently read data from basically any type of low power commercial sensors of the shelf. Major design drivers for the overall system are a high level of integration and high reliability.

scholarly journals Intelligent Wireless Sensors with Application to the Identification of Structural Modal Parameters and Steel Cable Forces: From the Lab to the Field

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Y. Lei ◽  
W. A. Shen ◽  
Y. Song ◽  
Y. Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensors ◽  
Wireless Sensor ◽  
Modal Parameters ◽  
Wireless Sensing ◽  
Steel Bridge ◽  
Steel Cable ◽  
Embedded Algorithms ◽  
Scalable Network

Wireless sensing systems have been proposed for structural heath monitoring in recent years. While wireless sensors are cost-competitive compared to tethered monitoring systems, their significant merit also lies in their embedded computational capabilities. In this paper, performance of the two embedded engineering algorithms, namely the fast Fourier transform and peak-picking algorithm implemented in the wireless sensing nodes codeveloped at Stanford University and the University of Michigan is investigated through laboratory and field experimental studies. Furthermore, the wireless sensor network embedded with the engineering algorithms is adopted for the identification of structural modal parameters and forces in steel bridge cables. Identification results by the embedded algorithms in the intelligent wireless sensors are compared with those obtained by conventional offline analysis of the measured time-history data. Such a comparison serves to validate the effectiveness of the intelligent wireless sensor network. In addition, it is shown that self-interrogation of measurement data based upon the two embedded algorithms in wireless sensor nodes greatly reduces the amount of data to be transmitted by the wireless sensing network. Thus, the intelligent wireless sensors offer scalable network solutions that are power-efficient for the health monitoring of civil infrastructures.

scholarly journals Construction of a Nonlinear Model of Tourism Economy Forecast Based on Wireless Sensor Network from the Perspective of Digital Economy

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jun Liu ◽  
Faxian Jia
Keyword(s):  
Prediction Model ◽  
Nonlinear Model ◽  
Circular Economy ◽  
Wireless Sensors ◽  
Regional Economy ◽  
Prediction Models ◽  
High Reliability ◽  
Wireless Sensor ◽  
Hysteresis Nonlinearity ◽  
Tourism Economy

With the outbreak of the new crown epidemic, the world economy has been severely tested, making predictions more difficult. Wireless sensors have the advantages of low cost, ease of use, high reliability, and high safety and have been widely used in the tourism economy. In order to understand the ability of wireless sensors to predict the regional economy, this article uses an example to construct a nonlinear model of wireless sensors to predict the regional economy. With the continuous development of the concept of circular economy, circular economy has gradually been recognized by Chinese scholars and practitioners. After domestic scholars continue to study the theory of circular economy, practicing the concept of circular economy and taking the road of sustainable development have become one of the important directions of the development of industrial theory. Literature analysis and other methods were used to conduct research on databases such as CNKI, Wan fang Database, and SSCI. Literature was collected, and GIS spatial analysis technology was used to analyze different areas and finally get a prediction model. The phenomenon is nonlinearity (such as saturation nonlinearity in the magnetic circuit), and some are caused by the nonlinear relationship between system variables (such as linear resistance and squared nonlinearity between current and power) and some artificially introduced nonlinear links (such as the hysteresis nonlinearity of relays). Experiments have proved that there is a certain error between the prediction model and the actual result; the error value is about 9%, which is less than the value of other prediction models. This shows that the output results of the nonlinear model of wireless sensor regional economic prediction should be processed reasonably. This result has a certain reference value, and its output should be combined with the actual situation. Related research found that under the nonlinear model, the more accurate and comprehensive the input value is, the closer the output result is to the actual value.

Ambient Energy Harvesting for Wireless Sensor Nodes: A Review

2014 ◽  
Vol 1025-1026 ◽  
pp. 1093-1098
Author(s):  
Mohamed Hanafiah bin Omar ◽  
Meng Hee Lim
Keyword(s):  
Energy Harvesting ◽  
Wireless Sensors ◽  
Business Processes ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensing ◽  
Power Devices ◽  
Wireless Sensor Nodes ◽  
Industrial Systems ◽  
Sensing Applications

Energy harvesting has generated a lot of interest in low power devices and wireless sensing applications as a viable replacement to the batteries that are required to power them. Wireless sensors nodes on the other hand have gain considerable interests from researchers and industries alike. Wireless sensing have the potential to improve productivity of industrial systems by providing greater awareness, control and integration of business processes. This paper attempts to provide an overview of the available technologies and at the same time deduce a practical energy harvesting platform as applied to wireless sensor nodes based on current research.

Implementation of a Cyber-Physical System Using Wireless Sensor Networks for Monitoring Patients

2015 ◽  
Vol 1 ◽  
pp. 26 ◽  
Author(s):  
Vo Que Son ◽  
Do Tan A
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Physical System ◽  
Patient Monitoring ◽  
High Reliability ◽  
Vital Signs ◽  
Wireless Sensor ◽  
Cyber Physical System ◽  
Self Administration ◽  
Hospital Units

Sensing, distributed computation and wireless communication are the essential building components of a Cyber-Physical System (CPS). Having many advantages such as mobility, low power, multi-hop routing, low latency, self-administration, utonomous data acquisition, and fault tolerance, Wireless Sensor Networks (WSNs) have gone beyond the scope of monitoring the environment and can be a way to support CPS. This paper presents the design, deployment, and empirical study of an eHealth system, which can remotely monitor vital signs from patients such as body temperature, blood pressure, SPO2, and heart rate. The primary contribution of this paper is the measurements of the proposed eHealth device that assesses the feasibility of WSNs for patient monitoring in hospitals in two aspects of communication and clinical sensing. Moreover, both simulation and experiment are used to investigate the performance of the design in many aspects such as networking reliability, sensing reliability, or end-to-end delay. The results show that the network achieved high reliability - nearly 97% while the sensing reliability of the vital signs can be obtained at approximately 98%. This indicates the feasibility and promise of using WSNs for continuous patient monitoring and clinical worsening detection in general hospital units.

Deep AI Enabled Ubiquitous Wireless Sensing

2021 ◽  
Vol 54 (2) ◽  
pp. 1-35
Author(s):  
Chenning Li ◽  
Zhichao Cao ◽  
Yunhao Liu
Keyword(s):  
Great Success ◽  
Wireless Sensing ◽  
Ubiquitous Sensing ◽  
Sensing Systems ◽  
The Status ◽  
Sensing Model ◽  
High Level ◽  
Traditional Approaches ◽  
The Internet Of Things ◽  
High Level Feature

With the development of the Internet of Things (IoT), many kinds of wireless signals (e.g., Wi-Fi, LoRa, RFID) are filling our living and working spaces nowadays. Beyond communication, wireless signals can sense the status of surrounding objects, known as wireless sensing , with their reflection, scattering, and refraction while propagating in space. In the last decade, many sophisticated wireless sensing techniques and systems were widely studied for various applications (e.g., gesture recognition, localization, and object imaging). Recently, deep Artificial Intelligence (AI), also known as Deep Learning (DL), has shown great success in computer vision. And some works have initially proved that deep AI can benefit wireless sensing as well, leading to a brand-new step toward ubiquitous sensing. In this survey, we focus on the evolution of wireless sensing enhanced by deep AI techniques. We first present a general workflow of Wireless Sensing Systems (WSSs) which consists of signal pre-processing, high-level feature, and sensing model formulation. For each module, existing deep AI-based techniques are summarized, further compared with traditional approaches. Then, we provide a view of issues and challenges induced by combining deep AI and wireless sensing together. Finally, we discuss the future trends of deep AI to enable ubiquitous wireless sensing.

scholarly journals Self-Organization of Activity in Wireless Sensor Networks

2005 ◽  
Vol 1 (2) ◽  
pp. 245-252 ◽  
Author(s):  
P. Davis ◽  
A. Hasegawa ◽  
N. Kadowaki ◽  
S. Obana
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Consumption ◽  
Wireless Sensors ◽  
Ad Hoc ◽  
Wireless Sensor ◽  
Self Organization ◽  
Sensor Systems ◽  
Low Resolution ◽  
Sensing Data

We propose a method for managing the spontaneous organization of sensor activity in ad hoc wireless sensor systems. The wireless sensors exchange messages to coordinate responses to requests for sensing data, and to control the fraction of sensors which are active. This method can be used to manage a variety of sensor activities. In particular, it can be used for reducing the power consumption by battery operated devices when only low resolution sensing is required, thus increasing their operation lifetimes.

High-Level Design of Wireless Sensor Networks for Performance Optimization Under Security Hazards

2017 ◽  
Vol 13 (3) ◽  
pp. 1-37 ◽  
Author(s):  
Pablo Peñil ◽  
Alvaro Díaz ◽  
Hector Posadas ◽  
Julio Medina ◽  
Pablo Sánchez
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Optimization ◽  
Wireless Sensor ◽  
Level Design ◽  
High Level

scholarly journals Design of Wireless Sensing Virtual Cloud Desktop System Based on ARM-Linux

2017 ◽  
Vol 13 (10) ◽  
pp. 123
Author(s):  
Chunqing Han ◽  
Lin Li
Keyword(s):  
Smart Home ◽  
Information Aggregation ◽  
Intelligent Transportation ◽  
Wireless Sensor ◽  
Wireless Sensing ◽  
Terminal Part ◽  
Individual Account ◽  
Wireless Terminal ◽  
System Data ◽  
Group Part

Aiming at exploring the wireless sensing network with mass processing in data collection, an embedded wireless sensor system based on ARM-Linux is put forward and designed. The whole system is mainly divided into wireless ZigBee sensing node group part, ARM data processing part, and virtual cloud desktop terminal part. Users’ terminal can be connected to the cloud system server through wired or wireless  ways. And it is possible to view user system data and wireless terminal data by logging in to an individual account. The results showed that the system can be applied in a lot of fields, such as intelligent transportation, health care, smart home and so on. Based on the above findings, it is concluded that it is important for information aggregation and remote fast monitoring.

Energy-Efficient Routing Techniques for Wireless Sensors Networks

2016 ◽  
pp. 37-62 ◽  
Author(s):  
Asmaa Osamaa ◽  
Shaimaa Ahmed El-Said ◽  
Aboul Ella Hassanien
Keyword(s):  
Wireless Sensors ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Efficient Routing ◽  
Routing Techniques ◽  
Physical Phenomena ◽  
And Storage ◽  
Innovative Techniques

Wireless sensor networks (WSNs), which normally consist of hundreds or thousands of sensor nodes each capable of sensing, processing, and transmitting environmental information, are deployed to monitor certain physical phenomena or to detect and track certain objects in an area of interests. The sensor nodes in WSN transmit data depending on local information and parameters such as signal strength, power consumption, location of data collection and accretion. Only reachable nodes are able to communicate with each other directly to collect and transmit data. The motes have limited energy resources along with constraints on its computational and storage capabilities. Thus, innovative techniques that eliminate energy inefficiencies that would shorten the lifetime of the network are highly required. Such constraints combined with a typical deployment of large number of sensor nodes pose many challenges to the design and management of WSNs and necessitate energy-awareness at all layers of the networking protocol stack. In this chapter, we present a survey of the state-of-the-art routing techniques in WSNs that take into consideration the energy issue.

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