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

Jangsik Bae, Meonghun Lee and Changsun Shin
Additional contact information
Jangsik Bae: Research Division, Shinhan A-Tec Co. Ltd., Changwon 51793, Korea
Meonghun Lee: Department of Agricultural Engineering, National Institute of Agricultural Sciences, Jeollabuk-do 55365, Korea
Changsun Shin: Department of Information and Communication Engineering, Sunchon National University, Jeollanam-do 57922, Korea

Sustainability, 2019, vol. 11, issue 21, 1-15

Abstract: With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO 2 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.

Keywords: fault detection; wireless sensor network; agricultural environment; microenvironment; oneM2M; internet of things (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/21/6171/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/21/6171/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:21:p:6171-:d:283719

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().