scholarly journals An Adaptive Genetic Algorithm of Adjusting Sensor Acquisition Frequency

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 990 ◽  
Author(s):  
Feng Chen ◽  
Shouzhi Xu ◽  
Ying Zhao ◽  
Hui Zhang
Keyword(s):  
Genetic Algorithm ◽  
Data Acquisition ◽  
Reducing Power ◽  
Sensor Nodes ◽  
Monitoring Data ◽  
Adaptive Genetic Algorithm ◽  
Environment Monitoring ◽  
Wireless Sensor Nodes ◽  
Acquisition Strategies

Portable meteorological stations are widely applied in environment monitoring systems, but they are always limited in power-supplying due to no cable power, especially in long-term monitoring scenarios. Reducing power consumption by adjusting a suitable frequency of sensor acquisition is very important for wireless sensor nodes. The regularity of historical environment data from a monitoring system is analyzed, and then an optimization model of an adaptive genetic algorithm for environment monitoring data acquisition strategies is proposed to lessen sampling frequency. According to the historical characteristics, the algorithm dynamically changes the recent data acquisition frequency so as to collect data with a smaller acquisition frequency, which will reduce the energy consumption of the sensor. Experiment results in a practical environment show that the algorithm can greatly reduce the acquisition frequency, and can obtain the environment monitoring data changing curve with less error compared with the high-frequency acquisition of fixed frequency.

WBAN Based Long Term ECG Monitoring

2013 ◽  
Vol 1 (3) ◽  
pp. 20-37 ◽  
Author(s):  
Marius Rosu ◽  
Sever Pasca
Keyword(s):  
Low Power ◽  
Sensor Nodes ◽  
Ecg Signal ◽  
Area Network ◽  
Wireless Sensor Nodes ◽  
Medication Process ◽  
Remote Healthcare ◽  
Electrocardiogram Ecg ◽  
Supply Information

Healthcare solutions using anytime, and anywhere remote healthcare surveillance devices, have become a major challenge. The patients with chronic diseases who need only therapeutic supervision are not advised to occupy a hospital bed. Using Wearable Wireless Body/Personal Area Network (WWBAN), intelligent monitoring of heart can supply information about medical conditions. Electrocardiogram (ECG) is the core reference in the diagnosis and medication process. An approach on healthcare solution WBAN based, for real-time ECG signal monitoring and long-term recording will be presented. Low-power wireless sensor nodes with local processing and encoding capabilities in order to achieve maximum mobility and flexibility are our main goal. ZigBee wireless technology will be used for transmission. Sensor device will be programmed to process locally the ECG signal and to raise an alert. Low-power and miniaturization are essential physical requirements.

scholarly journals Wireless Sensor Networks for Indoor Environment Monitoring Using LabVIEW

2011 ◽  
pp. 87-90
Author(s):  
Mrutyunjay Rout ◽  
Dr. Harish Kumar Verma ◽  
Subhashree Das
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Indoor Environment ◽  
Environmental Parameters ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Environment Monitoring ◽  
Wireless Sensor Nodes ◽  
Local Decision ◽  
Mems Technology

Wireless sensor networks (WSNs) have gained worldwide attention in recent years, particularly with the rapid progress in Micro-Electro-Mechanical Systems (MEMS) technology which has facilitated the development of smart sensors. These sensors are small, with limited processing and computing resources, and they are inexpensive compared to traditional sensors. These sensor nodes can sense, measure, and gather information from the environment and, based on some local decision process, they can transmit the sensed data to the user. WSNs are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communication capabilities. In present work we provide a brief summary of the state-ofthe- art in wireless sensor networks, investigate the feasibility of indoor environment monitoring using crossbow wireless sensor nodes. Here we used nesC programming language and TinyOS operating system for programming Crossbow sensor nodes and LabVIEW GUI is used for displaying different indoor environmental parameters such as temperature, humidity and light acquired from different Wireless sensor nodes. These sensor readings can help building administrators to monitor the physical conditions of the environment in a building for creating optimized energy usage.

Low-power wireless sensor nodes for ubiquitous long-term biomedical signal monitoring

2012 ◽  
Vol 50 (1) ◽  
pp. 20-27 ◽  
Author(s):  
Christian Bachmann ◽  
Maryam Ashouei ◽  
Valer Pop ◽  
Maja Vidojkovic ◽  
Harmke Groot ◽  
...  
Keyword(s):  
Low Power ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Biomedical Signal ◽  
Signal Monitoring

scholarly journals Dynamic Monitoring Of Agricultural Cultivation using IoT and Cloud Mechanism

2019 ◽  
Vol 8 (9) ◽  
pp. 556-560
Keyword(s):  
Data Analysis ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Monitoring System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Monitoring ◽  
Wireless Sensor Nodes ◽  
Acquisition Strategies

The objective of this work is a dynamic monitoring of agricultural cultivation using WSN technology. The Wireless Sensor nodes are designed in controlling and supervising the factors of variegated of such as level of water, humidity, and temperature. ZigBee mechanism is used as a medium of transmission in WSN (Wireless Sensor Network) devices using sensors, routers which propagate the data to longer distance over a network, with the help of coordinator sensor and will transmit the data to the cloud computer, which in turn will illustrate the control and data in the monitoring system. The node sensor will extract the factors of agriculture from various sources on realtime and will transmit the data using IoT (Internet of Things), which is integrated with one another on various platforms for performing various types of actions and will reduce the need of labor. Apart from monitoring, enhancement of details can be proposed based on WSN for the deployment of various nodes and by applying digital acquisition strategies for acquisition of data and performing various types of data analysis on cloud using the collected information of agriculture

WBAN Based Long Term ECG Monitoring

2018 ◽  
pp. 952-971 ◽  
Author(s):  
Marius Rosu ◽  
Sever Pasca
Keyword(s):  
Low Power ◽  
Sensor Nodes ◽  
Ecg Signal ◽  
Area Network ◽  
Wireless Sensor Nodes ◽  
Medication Process ◽  
Hospital Bed ◽  
Remote Healthcare ◽  
Electrocardiogram Ecg

Healthcare solutions using anytime, and anywhere remote healthcare surveillance devices, have become a major challenge. The patients with chronic diseases who need only therapeutic supervision are not advised to occupy a hospital bed. Using Wearable Wireless Body/Personal Area Network (WWBAN), intelligent monitoring of heart can supply information about medical conditions. Electrocardiogram (ECG) is the core reference in the diagnosis and medication process. An approach on healthcare solution WBAN based, for real-time ECG signal monitoring and long-term recording will be presented. Low-power wireless sensor nodes with local processing and encoding capabilities in order to achieve maximum mobility and flexibility are our main goal. ZigBee wireless technology will be used for transmission. Sensor device will be programmed to process locally the ECG signal and to raise an alert. Low-power and miniaturization are essential physical requirements.

Deployment of Context-Aware Sensor in Wireless Sensor Network Based on the Variants of Genetic Algorithm

2018 ◽  
Vol 8 (2) ◽  
pp. 1-24
Author(s):  
Puri Vishal ◽  
Ramesh Babu A.
Keyword(s):  
Genetic Algorithm ◽  
Network Connectivity ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensor Deployment ◽  
Adaptive Genetic Algorithm ◽  
Main Concern ◽  
Context Aware ◽  
Pollution Levels ◽  
Effective Network

Wireless sensor networks (WSNs) are generally a group of spatially scattered and devoted sensors to record and monitor the physical environmental condition, and the collected data is grouped at a central location. In fact, the environmental conditions such as sound, humidity, temperature, wind, pollution levels, etc., can be clearly determined by WSNs. The principal objective of WSNs is to organize the whole sensor nodes in their related positions, thereby developing an effective network. In WSNs, target COVerage (TCOV) and Network CONnectivity (NCON) are the main concern of the sensor deployment problem. Many research works aspire the evolvement of smart context awareness algorithm for sensor deployment issues in WSN. Here the TCOV and NCON process are deployed as the minimization problem. This article makes an analysis of different GA variations in attaining the objective. The GA variations are as follows: self-adaptive genetic algorithm (SAGA), deterministic-adaptive genetic algorithm (DAGA), Individual- Adaptive Genetic Algorithm (IAGA). Finally, the methods are compared to one another in terms of connectivity and coverage performance.

Attenuation Model of Antenna Signal with Barriers in Wireless Sensor Network

2013 ◽  
Vol 380-384 ◽  
pp. 3908-3911 ◽  
Author(s):  
Bo Xu ◽  
Shou Zhi Xu ◽  
Qing Wang ◽  
Ze Hua Chen
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Topology ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Monitoring Systems ◽  
Test Results ◽  
Environment Monitoring ◽  
Signal Attenuation ◽  
Wireless Sensor Nodes

Wireless sensor network (WSN) is widely applied to I-home, I-office, greenhouse agriculture, environment monitoring and many other industry areas. Signal attenuation and barriers make WSN hard to get high quality and reliability of network communication, which are very import to monitoring systems. This paper focus on the signal attenuation performance in WSN, analyzes the model of signal attenuation, and researches its performance with different signal transmitting distance and different barriers. According to test results, this paper gives the model of signal attenuation with the effect of barriers on transmitting. The results can apply to the distribution of wireless sensor nodes and the optimization of network topology.

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