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Spiking neural network in precision agriculture
Other Title(s)
الشبكة العصبية المتصاعدة في الزراعة الدقيقة
Joint Authors
Abbas, Hasna Ahmad
Shalta, Nadiyah Adnan
Source
Issue
Vol. 21, Issue 7 (31 Jul. 2015), pp.17-34, 18 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2015-07-31
Country of Publication
Iraq
No. of Pages
18
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN).
Soil moisture considered one of environment factors that effect on crop.
The period of irrigation must be monitored.
Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model.
This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN).
In this work, the precision agriculture system is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil.
In addition, to reduce power consumption of sensor nodes Modified Chain- Cluster based Mixed (MCCM) routing algorithm is used.
According to MCCM, the sensors will send their packets that are less than threshold moisture level to the sink.
The SNN with Modified Spike-Prop (MSP) training algorithm is capable of identifying soil, irrigation periods and monitoring the soil moisture level, this means that SNN has the ability to be an identifier and monitor.
By applying this system the particular agriculture area reaches to the desired moisture level.
American Psychological Association (APA)
Shalta, Nadiyah Adnan& Abbas, Hasna Ahmad. 2015. Spiking neural network in precision agriculture. Journal of Engineering،Vol. 21, no. 7, pp.17-34.
https://search.emarefa.net/detail/BIM-612792
Modern Language Association (MLA)
Shalta, Nadiyah Adnan& Abbas, Hasna Ahmad. Spiking neural network in precision agriculture. Journal of Engineering Vol. 21, no. 7 (Jul. 2015), pp.17-34.
https://search.emarefa.net/detail/BIM-612792
American Medical Association (AMA)
Shalta, Nadiyah Adnan& Abbas, Hasna Ahmad. Spiking neural network in precision agriculture. Journal of Engineering. 2015. Vol. 21, no. 7, pp.17-34.
https://search.emarefa.net/detail/BIM-612792
Data Type
Journal Articles
Language
English
Notes
Includes appendices : p. 23-34
Record ID
BIM-612792