31-10-2012, 11:10 AM
Greenhouse Monitoring with Wireless Sensor Network
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Abstract
In modern greenhouses, several measurement
points are required to trace down the local climate parameters
in different parts of the big greenhouse to make the greenhouse
automation system work properly. Cabling would make the
measurement system expensive and vulnerable. Moreover, the
cabled measurement points are difficult to relocate once they
are installed. Thus, a Wireless Sensor Network (WSN)
consisting of small-size wireless sensor nodes equipped with
radio and one or several sensors, is an attractive and costefficient
option to build the required measurement system.
In this work, we developed a wireless sensor node for
greenhouse monitoring by integrating a sensor platform
provided by Sensinode Ltd. [1] with three commercial sensors
capable to measure four climate variables. The feasibility of the
developed node was tested by deploying a simple sensor
network into Martens Greenhouse Research Foundation’s
greenhouse in Närpiö town in Western Finland. During a one
day experiment, we collected data to evaluate the network
reliability and its ability to detect the microclimate layers,
which typically exist in the greenhouse between lower and
upper flora. We were also able to show that the network can
detect the local differences in the greenhouse climate caused by
various disturbances, such as direct sunshine near the
greenhouse walls. This article is our first step in the area of
greenhouse monitoring and control, and it is all about the
developed sensor network feasibility and reliability. Data
analysis, control solutions and more complex network setups
will be left to be the main directions of our future work.
INTRODUCTION
The most important factors for the quality and
productivity of plant growth are temperature, humidity, light
and the level of the carbon dioxide. Continuous monitoring
of these environmental variables gives information to the
grower to better understand, how each factor affects growth
and how to manage maximal crop productiveness [2]. The
optimal greenhouse climate adjustment can enable us to
improve productivity and to achieve remarkable energy
savings - especially during the winter in northern countries
[3].
In the past generation greenhouses it was enough to have
one cabled measurement point in the middle to provide the
information to the greenhouse automation system. The
system itself was usually simple without opportunities to
control locally heating, lights, ventilation or some other
activity, which was affecting the greenhouse interior climate.
This all has changed in the modern greenhouses. The typical
size of the greenhouse itself is much bigger what it was
before, and the greenhouse facilities provide several options
to make local adjustments to the lights, ventilation, heating
and other greenhouse support systems. However, more
measurement data is also needed to make this kind of
automation system work properly. Increased number of
measurement points should not dramatically increase the
automation system cost. It should also be possible to easily
change the location of the measurement points according to
the particular needs, which depend on the specific plant, on
the possible changes in the external weather or greenhouse
structure and on the plant placement in the greenhouse.
RELATED WORK
The Rinnovando group [4] is doing research work in a
tomato greenhouse in the South of Italy. They are using
Sensicast devices for the air temperature, relativity humidity
and soil temperature measurements with wireless sensor
network. They have also developed a Web-based plant
monitoring application. Greenhouse grower can read the
measurements over the Internet, and an alarm will be sent to
his mobile phone by SMS or GPRS if some measurement
variable changes rapidly. The Rinnovando group has a test
bed in 20 x 50 meters tomato greenhouse. In their test bed,
six nodes are deployed into two rows 12.5 m apart from each
other. One mesh node works as a repeater and improves the
throughput of the communication. Bridge node gathers data
from other sensor nodes, which transmit the measurements
of temperature and relative humidity in one minute intervals
[4].
Liu et al. [5] have developed and tested a WSN prototype
for environmental monitoring inside the greenhouse. They
are using a star topology network of Crossbow MICAz
motes. The motes measure temperature, humidity and soil
moisture, and send their measurements to the sink node in
five minutes intervals. Sink node is a combination of MICAz
mote and MIB510 board with data terminal. The terminal
with ARM processor module shows the latest measurements
in LCD-screen inside the greenhouse and delivers the data to
the main PC by using GSM module. The central PC located
further apart from the network takes care of data logging and
processing. Mote programming and data receiving is
possible through the RS-232 serial interface provided by
MIB510 board. The Received Signal Strength Indicator
(RSSI) values over the distance between nodes with different
antenna heights and polarization angles were compared to
each other. Based on the results it was possible to conclude
that the longest communication range was achieved when
nodes had same orientation and maximal antenna height.
The temperature difference in experimental measurement
between two nodes, where one node was placed in the center
of the greenhouse and another near the greenhouse wall,
indicates the existence of the microclimate layers [5].
Sensors
Fast response time, low power consumption and
tolerance against moisture climate made SHT75 relative
humidity and temperature sensor [10] a perfect solution for
the greenhouse environment. Temperature accuracy of the
sensor is ±0.3 °C and the accuracy of the relative humidity
under ±2 %. Communication between SHT75 sensor and
node is similar to IIC interface developed by Philips. Data
and clock line are the same in both cases, but SHT75 has
only one pull-up resistor between data and power supply
line.
Luminosity was measured by TAOS TSL262R [11],
which converts light intensity to voltage. Unstable output
signal is handled by low-pass filter to get correct luminosity
values.
We mounted irradiance, temperature and humidity
sensors into four nodes, but Carbon dioxide sensor was
tricky because it sets special requirements for the input
voltage and the response time. Figaro’s TGS4161 [12]
carbon dioxide sensor (see Figure 4 on the right) was the
alternative, which was the most compatible with low voltage
sensor node. CO2 measuring takes longer time than other
measurements and CO2 sensor voltage supply must be within
±0.1V from the 5 Volts. The carbon dioxide value can be
read from the output voltage. Operation amplifier raises the
voltage level of otherwise weak signal from the sensor.
RESULTS
In our experimental setup, four nodes were deployed to
one greenhouse block to gather information about the
differences in climate variables between lower and upper
flora. Each node red temperature, humidity and irradiance
values once in four minute intervals over three hours. During
the experiment, the coordinator sent 200 data requests, and
each sensor node responded 50 times. Ten packets with
readings were either lost or received incorrectly. That
indicated 5% data loss rate in terms of packets. The maximal
communication range, 15 meters was figured out in
individual test where the distance between the coordinator
and the sensor node inside the greenhouse dense flora was
increased until the connection was lost. We also observed
that the reliable range in terms of tolerable packet loss was
approximately 10 meters. Compared to our previous
experiment in an open parking lot, the reliable
communication range fell to one third in the greenhouse’s
dense flora.
CONCLUSIONS AND FUTURE WORK
In this work, we integrated three commercial sensors
with Sensinode’s sensor platform to measure four
environmental key variables in greenhouse control. The
system feasibility was verified in a simple star topology
setup in a tomato greenhouse. We achieved up to 10 meter
communication range with tolerable 5% packet loss.
Because of the high humidity and dense tomato growth, the
reliable communication range was reduced to one third of
the respective communication range in open space. The
measurements also indicated that the system is able to detect
the local differences in the greenhouse environment, such as
different climate layers which exist from greenhouse bottom
to the top.
High moisture forced to consider the possible damages
and to protect sensitive boards carefully. When running the
experiments, another board damaging factor was noticed.
The pollen from the tomato flowers colored one of the black
plastic boxes yellow. Small particles of the pollen could also
block the measuring component of the sensors, affecting the
measuring results.