Computer Standards & Interfaces 35 (2013) 59–64.
Demonstrate a critical awareness of previous research in an IT context within a chosen topic area through a basic understanding of research theory and techniques.
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Computer Standards & Interfaces 35 (2013) 59–64.
Demonstrate a critical awareness of previous research in an IT context within a chosen topic area through a basic understanding of research theory and techniques.
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A survey on wireless sensor network infrastructure for agriculture
Xiaoqing Yu a,⁎, Pute Wu a,b, c
, Wenting Han a,b,c
, Zenglin Zhang a,c
a Northwest Agriculture and Forestry University, Shaanxi, Yangling, 712100, China
b National Engineering Research Center for Water Saving Irrigation at Yangling, Institute of Soil and Water Conservation of Chinese Academy of Sciences, Shaanxi, Yangling, 712100, China
c Research Institute of Water-saving Agriculture of Arid Regions of China, Shaanxi, Yangling, 712100, China
a b s t r a c ta r t i c l e i n f o
Article history:
Received 26 February 2012
Accepted 11 May 2012
Available online 18 May 2012
Keywords:
Hybrid wireless sensor network
Information collection
Agriculture
Wireless underground sensor network
Monitoring
The hybrid wireless sensor network is a promising application of wireless sensor networking techniques. The
main difference between a hybrid WSN and a terrestrial wireless sensor network is the wireless underground
sensor network, which communicates in the soil. In this paper, a hybrid wireless sensor network architecture
is introduced. The framework to deploy and operate a hybrid WSN is developed. Experiments were con-
ducted using a soil that was 50% sand, 35% silt, and 15% clay; it had a bulk density of 1.5 g/cm 3 and a specific
density of 2.6 cm− 3 . The experiment was conducted for several soil moistures (5, 10, 15, 20 and 25%) and
three signal frequencies (433, 868 and 915 MHz). The results show that the radio signal path loss is smallest
for low frequency signals and low moisture soils. Furthermore, the node deployment depth affected signal
attenuation for the 433 MHz signal. The best node deployment depth for effective transmission in a wireless
underground sensor network was determined.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
The environmental parameters of soil can be viewed as a type
of spatial and three-dimensional network information. Developing
methods to gather, process, integrate and apply environmental
information is the focus of agricultural environment information
technology and contemporary international agricultural science and
technology research. Because agricultural regions are scattered and
thus the terrains and environmental conditions vary significantly,
methods to collect crop growth environment variable information ac-
curately and rapidly are one of the primary problems for agricultural
environment information technology research [1].
Wireless sensor network (WSN) technology has emerged as the
technical means to solve the problem. A wireless sensor network in
an agricultural environment comprises integrated sensors deployed
in the area of the farmland. These sensors cooperate with each
other to perceive and monitor real-time soil and weather infor-
mation. The information is processed intelligently by an embedded
system. Moreover, the information is transmitted to a diagnosis deci-
sion center by a random self-organized wireless communication net-
work, which provides remote monitoring and management of the
agricultural environment. Recently, wireless sensor networks have
been extensively developed for agricultural environments [2,3]. The
networks have been used for irrigation, cultivation, fertilizer manage-
ment, etc.
Most wireless sensor networks developed for agricultural applica-
tions that involve soil monitoring are terrestrial wireless sensor net-
work systems. To avoid transmitting information through the soil,
the wireless sensor network is often connected by cables to data ac-
cess and wireless transceiver devices on the ground. These devices
are exposed and thus influence farming activities. In addition, trans-
mission from wireless nodes can be affected by natural geographical
and meteorological factors. Wireless underground sensor networks
(WUSN) provide a new method for underground monitoring [4–6]
and have become a new topic for research in the field of agricultural
environment information technology.
Wireless underground sensor networks are sensor networks that
comprise wireless underground sensor devices, which send and re-
ceive functional modules in the soil. These devices are located at spe-
cific soil depths and wirelessly transmit data. When the induction
module perceives data, the sensor network completes the process of
data perception and collection. The sensor network has several
merits: strong concealment, ease of deployment, timeliness of data,
reliability, and potential for coverage density. In addition to monitor-
ing static parameters of the soil, the wireless underground sensor
network can monitor soil motion such as landslides, earthquakes, de-
bris flow, movement of underground ice and volcanic eruptions [3].
Therefore, wireless underground sensor networks have the potential
for wide application in fields such as agriculture, military, transporta-
tion, structural engineering, and earth science [7,8].
Terrestrial wireless sensor networks in irrigation control systems
have been extensively developed and researched. However, the
wireless underground sensor network is a new research area without
definitive results [9,10]. In a hybrid WSN, a WSN and a WUSN are
Computer Standards & Interfaces 35 (2013) 59–64
⁎ Corresponding author.
E-mail address: yuxiaoqing115@gmail.com (X. Yu).
0920-5489/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.csi.2012.05.001
Contents lists available at SciVerse ScienceDirect
Computer Standards & Interfaces
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c s i
Xiaoqing Yu a,⁎, Pute Wu a,b, c
, Wenting Han a,b,c
, Zenglin Zhang a,c
a Northwest Agriculture and Forestry University, Shaanxi, Yangling, 712100, China
b National Engineering Research Center for Water Saving Irrigation at Yangling, Institute of Soil and Water Conservation of Chinese Academy of Sciences, Shaanxi, Yangling, 712100, China
c Research Institute of Water-saving Agriculture of Arid Regions of China, Shaanxi, Yangling, 712100, China
a b s t r a c ta r t i c l e i n f o
Article history:
Received 26 February 2012
Accepted 11 May 2012
Available online 18 May 2012
Keywords:
Hybrid wireless sensor network
Information collection
Agriculture
Wireless underground sensor network
Monitoring
The hybrid wireless sensor network is a promising application of wireless sensor networking techniques. The
main difference between a hybrid WSN and a terrestrial wireless sensor network is the wireless underground
sensor network, which communicates in the soil. In this paper, a hybrid wireless sensor network architecture
is introduced. The framework to deploy and operate a hybrid WSN is developed. Experiments were con-
ducted using a soil that was 50% sand, 35% silt, and 15% clay; it had a bulk density of 1.5 g/cm 3 and a specific
density of 2.6 cm− 3 . The experiment was conducted for several soil moistures (5, 10, 15, 20 and 25%) and
three signal frequencies (433, 868 and 915 MHz). The results show that the radio signal path loss is smallest
for low frequency signals and low moisture soils. Furthermore, the node deployment depth affected signal
attenuation for the 433 MHz signal. The best node deployment depth for effective transmission in a wireless
underground sensor network was determined.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
The environmental parameters of soil can be viewed as a type
of spatial and three-dimensional network information. Developing
methods to gather, process, integrate and apply environmental
information is the focus of agricultural environment information
technology and contemporary international agricultural science and
technology research. Because agricultural regions are scattered and
thus the terrains and environmental conditions vary significantly,
methods to collect crop growth environment variable information ac-
curately and rapidly are one of the primary problems for agricultural
environment information technology research [1].
Wireless sensor network (WSN) technology has emerged as the
technical means to solve the problem. A wireless sensor network in
an agricultural environment comprises integrated sensors deployed
in the area of the farmland. These sensors cooperate with each
other to perceive and monitor real-time soil and weather infor-
mation. The information is processed intelligently by an embedded
system. Moreover, the information is transmitted to a diagnosis deci-
sion center by a random self-organized wireless communication net-
work, which provides remote monitoring and management of the
agricultural environment. Recently, wireless sensor networks have
been extensively developed for agricultural environments [2,3]. The
networks have been used for irrigation, cultivation, fertilizer manage-
ment, etc.
Most wireless sensor networks developed for agricultural applica-
tions that involve soil monitoring are terrestrial wireless sensor net-
work systems. To avoid transmitting information through the soil,
the wireless sensor network is often connected by cables to data ac-
cess and wireless transceiver devices on the ground. These devices
are exposed and thus influence farming activities. In addition, trans-
mission from wireless nodes can be affected by natural geographical
and meteorological factors. Wireless underground sensor networks
(WUSN) provide a new method for underground monitoring [4–6]
and have become a new topic for research in the field of agricultural
environment information technology.
Wireless underground sensor networks are sensor networks that
comprise wireless underground sensor devices, which send and re-
ceive functional modules in the soil. These devices are located at spe-
cific soil depths and wirelessly transmit data. When the induction
module perceives data, the sensor network completes the process of
data perception and collection. The sensor network has several
merits: strong concealment, ease of deployment, timeliness of data,
reliability, and potential for coverage density. In addition to monitor-
ing static parameters of the soil, the wireless underground sensor
network can monitor soil motion such as landslides, earthquakes, de-
bris flow, movement of underground ice and volcanic eruptions [3].
Therefore, wireless underground sensor networks have the potential
for wide application in fields such as agriculture, military, transporta-
tion, structural engineering, and earth science [7,8].
Terrestrial wireless sensor networks in irrigation control systems
have been extensively developed and researched. However, the
wireless underground sensor network is a new research area without
definitive results [9,10]. In a hybrid WSN, a WSN and a WUSN are
Computer Standards & Interfaces 35 (2013) 59–64
⁎ Corresponding author.
E-mail address: yuxiaoqing115@gmail.com (X. Yu).
0920-5489/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.csi.2012.05.001
Contents lists available at SciVerse ScienceDirect
Computer Standards & Interfaces
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c s i
combined to form a WSN of mixed structure. The application of
hybrid WSNs to the monitoring of agriculture information is a novel
research topic.
The remainder of the paper is organized as follows. We provide an
overview of existing wireless sensor network techniques in Section 2.
The system architecture for the hybrid wireless sensor network is
presented in Section 3. In Section 4, the deployment and connectivity
of nodes are discussed. The experimental setup of a WUSN and its
analysis are described in Section 5. Finally, the paper is concluded in
Section 6.
2. Existing wireless sensor network techniques
2.1. Wireless sensor networks that monitor agricultural environments
Recently, wireless sensor networks have been deployed in agricul-
tural environments. Applications include the management of water
resources and product storage facilities, the determination of the
optimal time for crop harvest, the characterization of crop growth
and the prediction of fertilizer requirements.
In [11], a wireless sensor network was deployed to monitor the
water content, temperature and salinity of soil at a cabbage farm lo-
cated in Murcia, a semi-arid region of Spain. The wireless sensor net-
work deployed four types of structure nodes: soil, environmental,
water and gateway. The software and hardware components of each
node were fully described. The management and monitoring of the
system were performed by a central processing computer located in
the farm's management office. The system was tested in two stages:
a laboratory test and a field test. The purpose of the laboratory test
was to analyze the functionality of the system devices and to measure
the network's performance and energy consumption. The field test
assessed the range, robustness and reliability of the system.
In [12], the temperatures at various positions in a feed warehouse
were monitored using a wireless sensor network. The communication
frequency of the sensor nodes was 433 MHz, and the transmission
power was 10 mW. The results showed that temperature sensor
nodes buried at depths of 25 and 50 cm reliably transmitted temper-
ature signals to the gateway node; between 98.9% and 99.4% of the
signals were received by the gateway node. The data obtained from
monitoring were used to develop a model of the temperature at dif-
ferent positions in the feed storehouse; the accuracy of the model
predictions is between 90.0% and 94.3%.
The energy limitations of wireless sensor networks were the focus
of [13]. The number of nodes and the characteristics of the regional
distribution were used to determine reasonable clusters and the
communication's energy model. A theoretical analysis of the optimi-
zation of the number of clusters according to the different levels of
clusters was performed and experimentally verified. A wireless sen-
sor network was deployed to monitor a greenhouse environment in
[14]. The control terminal of the system was designed based on the
ARM9 and an embedded Linux operating system, which was used
for data receiving, real-time display and data storage. The control ter-
minal communicated with the remote management center using
GPRS. The wireless sensor network acquired the greenhouse environ-
ment data. The sensor network measured temperature, humidity, CO 2
content, light intensity, substrate temperature and the humidity of
the greenhouse using 6 channels.
A greenhouse wireless monitoring system was designed in [15]
using a wireless sensor network based on ZigBee. A dynamic wireless
sensor network with a star topology was proposed according to the
structure characteristics of the greenhouse. This low cost and low
power consumption design shortens the peer-to-peer communica-
tion distance by using mobile sink nodes to form a subnet with
child nodes based on time and frequency hopping methods. A com-
plex communication network based on the low power radio frequen-
cy chip NRF2401A was developed using the method of frame
expansion. The communication algorithms of the sensor, control
node and sink node were given. An energy consumption analysis of
the network child nodes was conducted using different working
states of the sink node.
A node system designed for the collection of farmland information
using a WSN was presented in [16]. This study combined wireless
sensor network nodes and sink nodes with an embedded processor
system. The network nodes were distributed regularly over the mon-
itored region and collected soil moisture data. The nodes formed the
network and transmitted the information to the sink nodes for dy-
namic display and storage. Several possible node antenna heights
were considered: 0.5, 1.0, 1.5 and 2.0 m. To study the transmission
distance of the radio signal in different growth periods, experiments
were conducted during three typical growth periods of wheat:
seeding, jointing and heading. The relationship between the effective
transmission distance of the radio signal in different growth periods
of wheat and the optimal antenna height was found. The results of
this research provide technical support for the application of wireless
sensor networks in agriculture.
A wireless sensor network was applied to water-saving irrigation
systems in [17]. A two-layer wireless sensor network was designed
based on irrigation needs and the characteristics of a fixed pipeline
spray irrigation system. An expression for the minimum number of
sensors required to cover the field was obtained using the relation-
ship between the sensing radius of each sensor and the range of the
shower nozzle. The data transmission method, the network structure
and the division of nodes were given. The reliability of the data trans-
mission was ensured using a layered fault diagnosis method.
2.2. Wireless underground sensor networks
Wireless underground sensor networks are a new research area.
At present, such networks are in the experimental study phase, and
no mature products are in the market. Little information has been
published on wireless underground sensor networks in agricultural
environments. The present work studies the dependence of path
loss, bit error rate and maximum transmission distance of the electro-
magnetic wave on factors such as soil type, volumetric water content
of the soil, deployment depth of nodes, internodes distance, the range
of frequency, etc.
A network system structure for a wireless underground sensor
network system designed as an intelligent transportation system for
the maintenance of the near surface soil (such as golf courses and
football fields) was designed in [13]. The software and hardware sys-
tems of the nodes were also designed. The collection nodes used a
low performance microcontroller. The receiving nodes on the ground
used a high performance microcontroller. However, development and
testing of the network system were not carried out. In addition, [13]
studied the performance of wireless underground sensor networks
that are influenced by the propagation of electromagnetic waves in
soil using the underground channel model, electrical characteristics
of soil and deployed solutions of wireless underground sensor net-
work nodes. Mathematical simulations were performed using
MATLAB for a system given as follows: 400 MHz signals, a sensor de-
ployment depth of 0.5 m, horizontal spacing between sensors of 1 m,
conductivity set to 0.1 and a dielectric constant of 10 under. The
transmission parameters of electromagnetic waves and energy losses
for different volumetric water contents of the soil and different sand
and clay soil compositions were studied.
In the laboratory of [18], wireless signal attenuation of a ZigBee
wireless transceiver module (Soil net) with a 2.44 GHz carrier fre-
quency was researched using soil columns of different soil types
and water contents. Experimental results showed that increases in
the soil column depth and volumetric water content of the soil in-
creased the signal attenuation. The relationship was expressed using
60 X. Yu et al. / Computer Standards & Interfaces 35 (2013) 59–64
hybrid WSNs to the monitoring of agriculture information is a novel
research topic.
The remainder of the paper is organized as follows. We provide an
overview of existing wireless sensor network techniques in Section 2.
The system architecture for the hybrid wireless sensor network is
presented in Section 3. In Section 4, the deployment and connectivity
of nodes are discussed. The experimental setup of a WUSN and its
analysis are described in Section 5. Finally, the paper is concluded in
Section 6.
2. Existing wireless sensor network techniques
2.1. Wireless sensor networks that monitor agricultural environments
Recently, wireless sensor networks have been deployed in agricul-
tural environments. Applications include the management of water
resources and product storage facilities, the determination of the
optimal time for crop harvest, the characterization of crop growth
and the prediction of fertilizer requirements.
In [11], a wireless sensor network was deployed to monitor the
water content, temperature and salinity of soil at a cabbage farm lo-
cated in Murcia, a semi-arid region of Spain. The wireless sensor net-
work deployed four types of structure nodes: soil, environmental,
water and gateway. The software and hardware components of each
node were fully described. The management and monitoring of the
system were performed by a central processing computer located in
the farm's management office. The system was tested in two stages:
a laboratory test and a field test. The purpose of the laboratory test
was to analyze the functionality of the system devices and to measure
the network's performance and energy consumption. The field test
assessed the range, robustness and reliability of the system.
In [12], the temperatures at various positions in a feed warehouse
were monitored using a wireless sensor network. The communication
frequency of the sensor nodes was 433 MHz, and the transmission
power was 10 mW. The results showed that temperature sensor
nodes buried at depths of 25 and 50 cm reliably transmitted temper-
ature signals to the gateway node; between 98.9% and 99.4% of the
signals were received by the gateway node. The data obtained from
monitoring were used to develop a model of the temperature at dif-
ferent positions in the feed storehouse; the accuracy of the model
predictions is between 90.0% and 94.3%.
The energy limitations of wireless sensor networks were the focus
of [13]. The number of nodes and the characteristics of the regional
distribution were used to determine reasonable clusters and the
communication's energy model. A theoretical analysis of the optimi-
zation of the number of clusters according to the different levels of
clusters was performed and experimentally verified. A wireless sen-
sor network was deployed to monitor a greenhouse environment in
[14]. The control terminal of the system was designed based on the
ARM9 and an embedded Linux operating system, which was used
for data receiving, real-time display and data storage. The control ter-
minal communicated with the remote management center using
GPRS. The wireless sensor network acquired the greenhouse environ-
ment data. The sensor network measured temperature, humidity, CO 2
content, light intensity, substrate temperature and the humidity of
the greenhouse using 6 channels.
A greenhouse wireless monitoring system was designed in [15]
using a wireless sensor network based on ZigBee. A dynamic wireless
sensor network with a star topology was proposed according to the
structure characteristics of the greenhouse. This low cost and low
power consumption design shortens the peer-to-peer communica-
tion distance by using mobile sink nodes to form a subnet with
child nodes based on time and frequency hopping methods. A com-
plex communication network based on the low power radio frequen-
cy chip NRF2401A was developed using the method of frame
expansion. The communication algorithms of the sensor, control
node and sink node were given. An energy consumption analysis of
the network child nodes was conducted using different working
states of the sink node.
A node system designed for the collection of farmland information
using a WSN was presented in [16]. This study combined wireless
sensor network nodes and sink nodes with an embedded processor
system. The network nodes were distributed regularly over the mon-
itored region and collected soil moisture data. The nodes formed the
network and transmitted the information to the sink nodes for dy-
namic display and storage. Several possible node antenna heights
were considered: 0.5, 1.0, 1.5 and 2.0 m. To study the transmission
distance of the radio signal in different growth periods, experiments
were conducted during three typical growth periods of wheat:
seeding, jointing and heading. The relationship between the effective
transmission distance of the radio signal in different growth periods
of wheat and the optimal antenna height was found. The results of
this research provide technical support for the application of wireless
sensor networks in agriculture.
A wireless sensor network was applied to water-saving irrigation
systems in [17]. A two-layer wireless sensor network was designed
based on irrigation needs and the characteristics of a fixed pipeline
spray irrigation system. An expression for the minimum number of
sensors required to cover the field was obtained using the relation-
ship between the sensing radius of each sensor and the range of the
shower nozzle. The data transmission method, the network structure
and the division of nodes were given. The reliability of the data trans-
mission was ensured using a layered fault diagnosis method.
2.2. Wireless underground sensor networks
Wireless underground sensor networks are a new research area.
At present, such networks are in the experimental study phase, and
no mature products are in the market. Little information has been
published on wireless underground sensor networks in agricultural
environments. The present work studies the dependence of path
loss, bit error rate and maximum transmission distance of the electro-
magnetic wave on factors such as soil type, volumetric water content
of the soil, deployment depth of nodes, internodes distance, the range
of frequency, etc.
A network system structure for a wireless underground sensor
network system designed as an intelligent transportation system for
the maintenance of the near surface soil (such as golf courses and
football fields) was designed in [13]. The software and hardware sys-
tems of the nodes were also designed. The collection nodes used a
low performance microcontroller. The receiving nodes on the ground
used a high performance microcontroller. However, development and
testing of the network system were not carried out. In addition, [13]
studied the performance of wireless underground sensor networks
that are influenced by the propagation of electromagnetic waves in
soil using the underground channel model, electrical characteristics
of soil and deployed solutions of wireless underground sensor net-
work nodes. Mathematical simulations were performed using
MATLAB for a system given as follows: 400 MHz signals, a sensor de-
ployment depth of 0.5 m, horizontal spacing between sensors of 1 m,
conductivity set to 0.1 and a dielectric constant of 10 under. The
transmission parameters of electromagnetic waves and energy losses
for different volumetric water contents of the soil and different sand
and clay soil compositions were studied.
In the laboratory of [18], wireless signal attenuation of a ZigBee
wireless transceiver module (Soil net) with a 2.44 GHz carrier fre-
quency was researched using soil columns of different soil types
and water contents. Experimental results showed that increases in
the soil column depth and volumetric water content of the soil in-
creased the signal attenuation. The relationship was expressed using
60 X. Yu et al. / Computer Standards & Interfaces 35 (2013) 59–64
a linear model, and the correlation coefficient, R 2 , was greater than
0.90.
The near surface wireless underground sensor network system
used for golf courses was developed and the acquisition nodes, relay
nodes and gateway node were designed in [19]. Each underground
acquisition node comprises a soil moisture sensor, controller, wireless
transceiver (Nordic NRF905, frequency 868 MHz), antenna, memory
unit and battery power module. Each collection node can connect
with several moisture sensors. Sink nodes are acquisition nodes
with no sensors that collect the data from acquisition nodes. Sink
nodes can communicate with other sink nodes and gateway nodes
in the routing algorithm. Gateway nodes control data storage and
the transmission of sink nodes and connect with a computer or
GPRS module using a RS232 interface. A gateway node can connect
with 31 sink nodes simultaneously, and it can be controlled remotely
and visited through DDI as sink nodes. Experimental results indicated
that the system operated normally, and soil moisture data at the dif-
ferent depths were transmitted to the central computer stably and
accurately.
In [20], Agnelo R and Silva studied how the communication per-
formance between terrestrial and underground nodes was impacted
by factors such as the antenna bandwidth of the WSN nodes in the
433 MHz frequency, the depth at which nodes are buried in the soil
(15 and 35 cm) and the water content of the soil (volumetric water
content was 9.5% and 37.3%). The field experiment showed that the
ultra-wideband antenna increased the communication range of the
original antennas by more than 350%. The transmission distance
dropped by 70% when the volumetric water content increased from
9.5% to 37.3%. When the deployment depth of the nodes changed
from 35 cm to 15 cm, the transmission distance of the signal for the
terrestrial nodes to the underground nodes (downlink transmission)
increased three times, and the transmission distance of the signal for
the underground nodes to the terrestrial nodes (uplink transmission)
only increased 0.4 times.
A center pivot sprayer was combined with wireless sensor net-
work nodes with a commercial full-wave 433 MHz magnetic antenna
for the precise irrigation of corn in [20]. Eight underground sensor ac-
quisition nodes (at a depth of 35–40 cm) were deployed circularly
within the operational range of the sprayer, and a signal receiving
node (2.5 m from the ground level) was installed in the sprayer. In
this paper, the influence of ground cover, corn canopy and the rota-
tion speed of the sprayer on receiving information was analyzed.
In [21], distortion of the acquisition signal of the soil's moisture
was greatly impacted by rainfall and stormy weather conditions,
soil compactness, soil density, vegetation cover, topology structure
parameters of the wireless underground sensor network, sampling
time and sampling density.
Mehmet C. Vuran studied the channel model of wireless sensor
network electromagnetic wave transmission in soil in [21]. He ana-
lyzed path loss, bit error ratio, maximum transmission distance and
the water content test error of electromagnetic wave transmission
under variable conditions, such as the composition of the soil, volu-
metric water content of the soil (5%–25%), node deployment depth
(0.1 m–2 m), internode distance (0.5 m–5 m), and frequency
(300 MHz–900 MHz). The signal attenuation and antenna size results
showed that frequencies between 300 MHz and 400 MHz were more
suitable for wireless underground sensor networks. Because the
transmission distance was influenced by the deployment depth, no
one frequency is the optimum, and WUSNs based on many frequency
cognitive radio techniques are more adaptable to environmental
changes. For networks that have shallow nodes, the double path
channel model can be used. The single path channel model can be
used for networks that have deeply buried nodes. The topology struc-
ture of the sensor networks can be designed according to the node
deployment depth. The maximum transmission distance was 5 m
under the 300 MHz–400 MHz frequency. Therefore, multiple hop
transmissions are suitable in the WUSN. Soil water content had a sig-
nificant influence on the performance of the networks. The WUSN
must be more robust to changes in water content to be suitable for
monitoring soil parameters. The performance of the wireless sensor
network was also affected by seasonal environment changes; cross
layer communication methods might solve this problem.
3. System architecture
An information collection system uses sensors to collect soil infor-
mation, including temperature and water content. To collect soil in-
formation, the WSN uses the CC2430 wireless transceiver module
based on the ZigBee agreement. The WUSN uses the nRF905 wireless
chip to collect and transmit information.
The wireless sensor node was designed using a modular design
method. The architecture of the terrestrial WSN is shown in Fig. 1.
The WUSN uses a nRF905 wireless chip instead of a CC2430 RF chip.
Each node comprises a sensor module, processor module, wireless
communication module and energy supply module.
The network topology structure is the foundation of the network.
A good network topology structure should consider the specific appli-
cation and have a simple, reliable and effective implementation
[22–24]. The proposed design combines the terrestrial and under-
ground wireless sensor network structures. A traditional WSN is
adopted above depths of 40 cm, and a WUSN is adopted below depths
of 40 cm. The sink node of the WUSN is on the ground. All nodes in
the WUSN will transmit data to the terrestrial sink node, which better
conceals the network. The location of a WUSN node depends on the
specific application. It can be located at the same depth, at a different
depth or as a different layer. The sink node can be fixed or movable
but must remain in the range of communication. The topological
structure is shown in Fig. 2.
4. Deployment and connectivity of nodes
To monitor the water content of the soil in real time, signal acqui-
sition nodes are buried in and below the cultivate layer. The hybrid
wireless sensor network node and sensor are deployed as shown in
Fig. 3.
The unique channel characteristics and heterogeneous network
architecture of the WUSN complicate the connectivity analysis. In
particular, there are three communication channels, based on the lo-
cations of the transmitter and the receiver, in a WUSN: underground-
to-underground, underground-to-aboveground, and aboveground-
to-underground.
As shown in Fig. 4, a WUSN comprises underground sensors
deployed in the sensing field, fixed aboveground data sinks set around
Various
sensors AD/
DA
CC2430
/nRF905
RF chip
CPU
Storage
Sensing Model
Processing Model Communication model
Network
MAC
Power Model
Fig. 1. Architecture of the wireless sensor network node.
61X. Yu et al. / Computer Standards & Interfaces 35 (2013) 59–64
0.90.
The near surface wireless underground sensor network system
used for golf courses was developed and the acquisition nodes, relay
nodes and gateway node were designed in [19]. Each underground
acquisition node comprises a soil moisture sensor, controller, wireless
transceiver (Nordic NRF905, frequency 868 MHz), antenna, memory
unit and battery power module. Each collection node can connect
with several moisture sensors. Sink nodes are acquisition nodes
with no sensors that collect the data from acquisition nodes. Sink
nodes can communicate with other sink nodes and gateway nodes
in the routing algorithm. Gateway nodes control data storage and
the transmission of sink nodes and connect with a computer or
GPRS module using a RS232 interface. A gateway node can connect
with 31 sink nodes simultaneously, and it can be controlled remotely
and visited through DDI as sink nodes. Experimental results indicated
that the system operated normally, and soil moisture data at the dif-
ferent depths were transmitted to the central computer stably and
accurately.
In [20], Agnelo R and Silva studied how the communication per-
formance between terrestrial and underground nodes was impacted
by factors such as the antenna bandwidth of the WSN nodes in the
433 MHz frequency, the depth at which nodes are buried in the soil
(15 and 35 cm) and the water content of the soil (volumetric water
content was 9.5% and 37.3%). The field experiment showed that the
ultra-wideband antenna increased the communication range of the
original antennas by more than 350%. The transmission distance
dropped by 70% when the volumetric water content increased from
9.5% to 37.3%. When the deployment depth of the nodes changed
from 35 cm to 15 cm, the transmission distance of the signal for the
terrestrial nodes to the underground nodes (downlink transmission)
increased three times, and the transmission distance of the signal for
the underground nodes to the terrestrial nodes (uplink transmission)
only increased 0.4 times.
A center pivot sprayer was combined with wireless sensor net-
work nodes with a commercial full-wave 433 MHz magnetic antenna
for the precise irrigation of corn in [20]. Eight underground sensor ac-
quisition nodes (at a depth of 35–40 cm) were deployed circularly
within the operational range of the sprayer, and a signal receiving
node (2.5 m from the ground level) was installed in the sprayer. In
this paper, the influence of ground cover, corn canopy and the rota-
tion speed of the sprayer on receiving information was analyzed.
In [21], distortion of the acquisition signal of the soil's moisture
was greatly impacted by rainfall and stormy weather conditions,
soil compactness, soil density, vegetation cover, topology structure
parameters of the wireless underground sensor network, sampling
time and sampling density.
Mehmet C. Vuran studied the channel model of wireless sensor
network electromagnetic wave transmission in soil in [21]. He ana-
lyzed path loss, bit error ratio, maximum transmission distance and
the water content test error of electromagnetic wave transmission
under variable conditions, such as the composition of the soil, volu-
metric water content of the soil (5%–25%), node deployment depth
(0.1 m–2 m), internode distance (0.5 m–5 m), and frequency
(300 MHz–900 MHz). The signal attenuation and antenna size results
showed that frequencies between 300 MHz and 400 MHz were more
suitable for wireless underground sensor networks. Because the
transmission distance was influenced by the deployment depth, no
one frequency is the optimum, and WUSNs based on many frequency
cognitive radio techniques are more adaptable to environmental
changes. For networks that have shallow nodes, the double path
channel model can be used. The single path channel model can be
used for networks that have deeply buried nodes. The topology struc-
ture of the sensor networks can be designed according to the node
deployment depth. The maximum transmission distance was 5 m
under the 300 MHz–400 MHz frequency. Therefore, multiple hop
transmissions are suitable in the WUSN. Soil water content had a sig-
nificant influence on the performance of the networks. The WUSN
must be more robust to changes in water content to be suitable for
monitoring soil parameters. The performance of the wireless sensor
network was also affected by seasonal environment changes; cross
layer communication methods might solve this problem.
3. System architecture
An information collection system uses sensors to collect soil infor-
mation, including temperature and water content. To collect soil in-
formation, the WSN uses the CC2430 wireless transceiver module
based on the ZigBee agreement. The WUSN uses the nRF905 wireless
chip to collect and transmit information.
The wireless sensor node was designed using a modular design
method. The architecture of the terrestrial WSN is shown in Fig. 1.
The WUSN uses a nRF905 wireless chip instead of a CC2430 RF chip.
Each node comprises a sensor module, processor module, wireless
communication module and energy supply module.
The network topology structure is the foundation of the network.
A good network topology structure should consider the specific appli-
cation and have a simple, reliable and effective implementation
[22–24]. The proposed design combines the terrestrial and under-
ground wireless sensor network structures. A traditional WSN is
adopted above depths of 40 cm, and a WUSN is adopted below depths
of 40 cm. The sink node of the WUSN is on the ground. All nodes in
the WUSN will transmit data to the terrestrial sink node, which better
conceals the network. The location of a WUSN node depends on the
specific application. It can be located at the same depth, at a different
depth or as a different layer. The sink node can be fixed or movable
but must remain in the range of communication. The topological
structure is shown in Fig. 2.
4. Deployment and connectivity of nodes
To monitor the water content of the soil in real time, signal acqui-
sition nodes are buried in and below the cultivate layer. The hybrid
wireless sensor network node and sensor are deployed as shown in
Fig. 3.
The unique channel characteristics and heterogeneous network
architecture of the WUSN complicate the connectivity analysis. In
particular, there are three communication channels, based on the lo-
cations of the transmitter and the receiver, in a WUSN: underground-
to-underground, underground-to-aboveground, and aboveground-
to-underground.
As shown in Fig. 4, a WUSN comprises underground sensors
deployed in the sensing field, fixed aboveground data sinks set around
Various
sensors AD/
DA
CC2430
/nRF905
RF chip
CPU
Storage
Sensing Model
Processing Model Communication model
Network
MAC
Power Model
Fig. 1. Architecture of the wireless sensor network node.
61X. Yu et al. / Computer Standards & Interfaces 35 (2013) 59–64
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