The analysis and design of the modified PIFA on the wearable sensor nodes

2011 ◽  
Author(s):  
Y.-C. Kan ◽  
H.-C. Chiu ◽  
P.-K. Huang
Keyword(s):  
Sensor Nodes ◽  
Wearable Sensor ◽  
Analysis And Design

Autonomous Wearable Sensor Nodes With Flexible Energy Harvesting

2014 ◽  
Vol 14 (7) ◽  
pp. 2299-2306 ◽  
Author(s):  
Wang Yun Toh ◽  
Yen Kheng Tan ◽  
Wee Song Koh ◽  
Liter Siek
Keyword(s):  
Energy Harvesting ◽  
Sensor Nodes ◽  
Wearable Sensor

scholarly journals Classifier-Based Data Transmission Reduction in Wearable Sensor Network for Human Activity Monitoring

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 85
Author(s):  
Marcin Lewandowski ◽  
Bartłomiej Płaczek ◽  
Marcin Bernas
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Activity Recognition ◽  
Human Activity ◽  
Network Lifetime ◽  
Data Transmission ◽  
Activity Monitoring ◽  
Sensor Nodes ◽  
Wearable Sensor ◽  
Transmission Reduction

The recent development of wireless wearable sensor networks offers a spectrum of new applications in fields of healthcare, medicine, activity monitoring, sport, safety, human-machine interfacing, and beyond. Successful use of this technology depends on lifetime of the battery-powered sensor nodes. This paper presents a new method for extending the lifetime of the wearable sensor networks by avoiding unnecessary data transmissions. The introduced method is based on embedded classifiers that allow sensor nodes to decide if current sensor readings have to be transmitted to cluster head or not. In order to train the classifiers, a procedure was elaborated, which takes into account the impact of data selection on accuracy of a recognition system. This approach was implemented in a prototype of wearable sensor network for human activity monitoring. Real-world experiments were conducted to evaluate the new method in terms of network lifetime, energy consumption, and accuracy of human activity recognition. Results of the experimental evaluation have confirmed that, the proposed method enables significant prolongation of the network lifetime, while preserving high accuracy of the activity recognition. The experiments have also revealed advantages of the method in comparison with state-of-the-art algorithms for data transmission reduction.

scholarly journals Wearable Sensor Clothing for Body Movement Measurement during Physical Activities in Healthcare

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2068
Author(s):  
Armands Ancans ◽  
Modris Greitans ◽  
Ricards Cacurs ◽  
Beate Banga ◽  
Artis Rozentals
Keyword(s):  
Inertial Sensor ◽  
Body Movement ◽  
The Body ◽  
Sensor Nodes ◽  
Digital Cameras ◽  
Wearable Sensor ◽  
Wireless System ◽  
Acquisition Device ◽  
Set Up ◽  
Application Specific

This paper presents a wearable wireless system for measuring human body activities, consisting of small inertial sensor nodes and the main hub for data transmission via Bluetooth for further analysis. Unlike optical and ultrasonic technologies, the proposed solution has no movement restrictions, such as the requirement to stay in the line of sight, and it provides information on the dynamics of the human body’s poses regardless of its location. The problem of the correct placement of sensors on the body is considered, a simplified architecture of the wearable clothing is described, an experimental set-up is developed and tests are performed. The system has been tested by performing several physical exercises and comparing the performance with the commercially available BTS Bioengineering SMART DX motion capture system. The results show that our solution is more suitable for complex exercises as the system based on digital cameras tends to lose some markers. The proposed wearable sensor clothing can be used as a multi-purpose data acquisition device for application-specific data analysis, thus providing an automated tool for scientists and doctors to measure patient’s body movements.

A Wideband Slot Antenna in a Box for Wearable Sensor Nodes

2015 ◽  
Vol 14 ◽  
pp. 1494-1497 ◽  
Author(s):  
Mohammad Vatankhah Varnoosfaderani ◽  
David V. Thiel ◽  
Jun Wei Lu
Keyword(s):  
Sensor Nodes ◽  
Slot Antenna ◽  
Wearable Sensor

Design of Hybrid Ambient Energy Harvesting Antenna for Wireless Sensor Nodes

2014 ◽  
Vol 687-691 ◽  
pp. 3387-3390
Author(s):  
Lei Jun Xu ◽  
Chang Shuo Wang ◽  
Bai Xue
Keyword(s):  
Energy Harvesting ◽  
Sensor Nodes ◽  
Maintenance Cost ◽  
Wireless Sensor Nodes ◽  
Hybrid Energy ◽  
Analysis And Design ◽  
Novel Structure ◽  
Energy Harvesting System ◽  
The Cost ◽  
Hybrid Energy Harvesting

To the high maintenance cost for changing wireless sensor’s battery in Internet of Things (IoT), a hybrid ambient energy harvesting system for wireless sensor’s power supply is proposed. The system can collect the ambient RF energy, vibration energy and light energy, converts them into DC supply. This paper focuses on the analysis and design of the hybrid energy harvesting antenna, using a novel structure to combine three energy receivers in one antenna, which reduces the size and the cost effectively. The antenna operates at both 3G mobile frequency (1.9GHz) and 4G mobile frequency (2.6GHz), the measured input return loss is 24.3dB and 19.9dB, respectively.

HUMAN ACTIVITY RECOGNITION BY FUSING MULTIPLE SENSOR NODES IN THE WEARABLE SENSOR SYSTEMS

2012 ◽  
Vol 12 (05) ◽  
pp. 1250084 ◽  
Author(s):  
YONGCAI GUO ◽  
WEIHUA HE ◽  
CHAO GAO
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Sensor Node ◽  
Recognition Rate ◽  
Fusion Rule ◽  
Sensor Nodes ◽  
Sensor Systems ◽  
Wearable Sensor ◽  
Activity Data ◽  
Multiple Sensor

This paper presents a novel method for recognizing human daily activity by fusion multiple sensor nodes in the wearable sensor systems. The procedure of this method is as follows: firstly, features are extracted from each sensor node and subsequently reduced in dimension by generalized discriminant analysis (GDA), to ensure the real-time performance of activity recognition; then, the reduced features are classified with the multiclass relevance vector machines (RVM); finally, the individual classification results are fused at the decision level, in consideration that the different sensor nodes can provide heterogeneous and complementary information about human activity. Extensive experiments have been carried out on Wearable Action Recognition Database (WARD). Experimental results show that if all the five sensor nodes are fused with the adaptive weighted logarithmic opinion pools (WLOGP) fusion rule, we can even achieve a recognition rate as high as 98.78%, which is far more better than the situations where only single sensor node is available or the activity data is processed by state-of-the-art methods. Moreover, this proposed method is flexible to extension, and can provide a guideline for the construction of the minimum desirable system.

scholarly journals Analysis and Design of a Wireless Sensor Network Based on the Residual Energy of the Nodes and the Harvested Energy from Mint Plants

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Hassel Aurora Alcalá-Garrido ◽  
Víctor Barrera-Figueroa ◽  
Mario E. Rivero-Ángeles ◽  
Yunia Verónica García-Tejeda ◽  
Hosanna Ramírez Pérez
Keyword(s):  
Continuous Monitoring ◽  
Residual Energy ◽  
Wireless Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Analysis And Design ◽  
Report Data ◽  
Energy Harvesting System ◽  
To Receive ◽  
Discrete Markov Chain

Nowadays, the use of sensor nodes for the IoT is widespread; nodes that compose these networks must possess self-organizing capabilities and communication protocols that require less energy consumption during communication procedures. In this work, we propose the design and analysis of an energy harvesting system using bioelectricity harvested from mint plants that aids in powering a particular design of a wireless sensor operating in a continuous monitoring mode. The system is based on randomly turning nodes ON (active nodes) and OFF (inactive nodes) to avoid their energy depletion. While a node is in an inactive state, it is allowed to harvest energy from the surroundings. However, while the node is harvesting energy from its surroundings, it is unable to report data. As such, a clear compromise is established between the amount of information reported and the lifetime of the network. To finely tune the system’s parameters and offer an adequate operation, we derive a mathematical model based on a discrete Markov chain that describes the main dynamics of the system. We observe that with the use of mint plants, the harvested energy is of the order of a few Joules; nonetheless, such small energy values can sustain a wireless transmission if correctly adapted to drive a wireless sensor. If we consider the lowest mean harvested energy obtained from mint plants, such energy can be used to transmit up to 259,564 bits or can also be used to receive up to 301,036 bits. On the other hand, if we consider the greatest mean harvested energy, this energy can be used to transmit up to 2,394,737 bits or can also be used to receive up to 2,777,349 bits.

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