IEEE Consumer Electronics Magazine - July/August 2021 - 66

Smart Agriculture
Figure 3. Deployed sensor node block diagram of
FarmFox.
Figure 4. Field setup with FarmFox at the test location.
moisture, temperature, turbidity, and pH. These
parameters help in monitoring the soil health,
which can be utilized to the advantage of the
farmers for a better yield. Figure 4 illustrates the
four sensors used for developing FarmFox,
namely V2 soil moisture sensor, soil temperature
sensor DS18B20, turbidity sensor, and soil pH
sensor. As mentioned before, these sensors are
connected to Arduino Nano R3, which can be
placed to a maximum depth of 20 cm in the soil
to measure the moisture, temperature, and pH.
The turbidity sensors are placed in the field in
an exquisite manner that can measure the cloudiness
of the water used for irrigation purposes.
Turbidity along with the pH measurement may
state the current soil health to the analyzer. This
shows that FarmFox is a robust system.
Integrated Design of the IoT Gateway
In any IoT environment, IoT gateway plays an
important role. It acts as a communication bridge,
connecting the sensors to the Internet, Bluetooth
devices with built-in cloud interface, etc. It also
helps in latency reduction and capacity enhancement
at the edge by prehandling the raw data. In
FarmFox, an IoT gateway is used to transfer the
data from the field to the sink node for the analysis
of data. Two highly used protocols namely Wi-Fi
and TCP are used to meet the said purpose. We
have designed a website for controlling and monitoring
the sensors. It also helps in the retrieval of
sensor data. Every gateway is assigned with a randomly
generated unique user ID after we sign up
on the website. We have used a solar panel along
with a Li-ion battery to power up the sensor nodes.
Implementation of Remote Servers
In our design, we have developed two different
servers: 1) repository server and 2) web server.
The repository servers are used as the central
server system that stores all the data, both
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relevant and irrelevant, whereas the web server is
used to store webserver software and website's
component files. The servers are hosted in a cloud
medium. The use of these two servers enables the
FarmFox system to monitor the soil health
remotely, which makes it a " one of a kind " system
for precision agriculture.
IMPLEMENTATION OF FarmFox
We implanted and deployed FarmFox in the
crop fields near CIET, BudBud campus
(23.4078236, 87.5529721), Burdwan District, West
Bengal, India. Experimental setup is shown in
Figure 4. The experiment has been carried out
within January 2020 to March 2020. Soil health
monitoring is divided into two sections-a) data
aggregation and b) data transmission.
Data Sensing and Data Aggregation
Data sensing and data aggregation is the most
intrinsic part of the whole process. In this process,
the sensor nodes measure the changes in stimuli
light, heat, sound, motion, magnetic field, etc., and
then converts them into electrical signals. These
changes are passed through an interface to convert
it into binary format and then after processing
we get the reading. The sensors deployed in the
case study area, collect data about moisture, temperature,
turbidity, and pH of the soil, which is
then stored in the in-built EPROM of 512 B of the
FarmFox system. The sensed data are immediately
fed to a connected cloud source. Hence, the aggregate
can be accessed remotely with a PC having an
internet connection. The uniqueness of the FarmFox
model is that, in absence of a healthy internet
connection, sensed data will not be lost, rather
it will be stored in the EPROM. Upon, restoration
of the internet connection, the data will be
uploaded in the cloud storage. Hence, time-series
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