Design of Tungsten Tailing Reservoir Safety Monitoring and Warning System Based on Wireless Sensor Networks and LabVIEW

2013 ◽  
Vol 427-429 ◽  
pp. 1268-1271
Author(s):  
Xue Wen He ◽  
Ying Fei Sheng ◽  
Kuan Gang Fan ◽  
Le Ping Zheng ◽  
Qing Mei Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Communication Protocol ◽  
Warning System ◽  
Safety Monitoring ◽  
Wireless Sensor ◽  
Serial Port ◽  
Rf Transceiver ◽  
New Type

In view of the existing flaws of traditional manual observations, a new type of tailing reservoir safety monitoring and warning system based on ZigBee and LabVIEW was designed. The system chose SoC chip CC2530 as the RF transceiver and designed the low-power wireless sensor networks nodes to collect and process the data of tailing reservoir. It chose ZigBee 2007 as the network communication protocol, and uploaded the data to PC by RS232 serial port. The monitoring and warning interface of PC was completed with LabVIEW. The testing results show that the data transmission of the network is stable and the system is suitable for real-time monitoring and warning of the tungsten tailing reservoir.

WiseNET, an Ultra Low-Power RF Transceiver SoC and Communication Protocol Solution for Wireless Sensor Networks

2006 ◽  
pp. 345-375
Author(s):  
Vincent Peiris ◽  
Amre El Hoiydi ◽  
Antoine Ribordy ◽  
Erwan Le Roux ◽  
Thierry Melly ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Low Power ◽  
Communication Protocol ◽  
Wireless Sensor ◽  
Rf Transceiver ◽  
Ultra Low Power

An Energy Efficient Routing Approach to Enhance Coverage for Application Specific Wireless Sensor Networks using Genetic Algorithm

2019 ◽  
Vol 13 ◽  
Author(s):  
Amandeep Kaur Sohal ◽  
Ajay Kumar Sharma ◽  
Neetu Sood
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Cluster Formation ◽  
Green Computing ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors. Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption. Method: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm. Conclusion: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

A Small World Routing Protocol in Wireless Sensor Networks

2011 ◽  
Vol 474-476 ◽  
pp. 828-833
Author(s):  
Wen Jun Xu ◽  
Li Juan Sun ◽  
Jian Guo ◽  
Ru Chuan Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Small World ◽  
Wireless Sensor ◽  
Small World Network ◽  
Average Delay ◽  
Network Diameter ◽  
Simulation Results

In order to reduce the average path length of the wireless sensor networks (WSNs) and save the energy, in this paper, the concept of the small world is introduced into the routing designs of WSNs. So a new small world routing protocol (SWRP) is proposed. By adding a few short cut links, which are confined to a fraction of the network diameter, we construct a small world network. Then the protocol finds paths through recurrent propagations of weak and strong links. The simulation results indicate that SWRP reduces the energy consumption effectively and the average delay of the data transmission, which leads to prolong the lifetime of both the nodes and the network.

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