An Agreement-Based Fault Detection Mechanism for Under Water Sensor Networks

2007 ◽  
Author(s):  
Pu Wang ◽  
Jun Zheng ◽  
Cheng Li
Keyword(s):  
Sensor Networks ◽  
Fault Detection ◽  
Detection Mechanism ◽  
Water Sensor

scholarly journals An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

Sensors ◽  
2014 ◽  
Vol 14 (5) ◽  
pp. 7655-7683 ◽  
Author(s):  
Yang Yang ◽  
Zhipeng Gao ◽  
Hang Zhou ◽  
Xuesong Qiu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Wireless Sensor ◽  
Detection Mechanism ◽  
Distributed Fault Detection

Cost-Effective Lock-Stepped EDDI: Transient Fault Detection Mechanism

2012 ◽  
Vol 35 (12) ◽  
pp. 2562
Author(s):  
Chao WANG ◽  
Zhong-Chuan FU ◽  
Hong-Song CHEN ◽  
Gang CUI
Keyword(s):  
Fault Detection ◽  
Cost Effective ◽  
Detection Mechanism ◽  
Transient Fault

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.

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