IEEE Consumer Electronics Magazine - July/August 2021 - 59

using cyber-physical system (CPS).3 In the work
by Saiz-Rubio and Rovira-Mas,1 the status of the
advanced farm management systems is reviewed
and an insight into the crucial steps needed for
sustainable agriculture is given. The following
article emphasizes the IoT-enabled automation
of rose farming inside a greenhouse.
CHALLENGES OF TRADITIONAL
GREENHOUSE FARMING
The proportion of nutrients made available:
Conventional farming incurs manual labor and
consumes a great amount of time, hence at
times, it is not possible to feed the plant with
the desired amount of nutrients (NPK), which
slows down the growth of the plants and does
not give proper yield.
Temperature and Humidity: Excess high
temperature and humidity affect the development
of leaves and shoots adversely. It also
results in discoloration of the petals and the
blackening of the leaves. Higher temperature
also affects the size of the flower and fewer
and smaller petals.
Accurate monitoring of the soil and its moisture:
Too little moisture can result in yield loss
and plant death and too much of it causes root
diseases and wasted water. It is seen that the
bare-dry or over-wet soils may damage the
roots of the rose plants; hence, rich and welldraining
soil is required for better and quality
produce.
Detection and prevention from diseases:Rose
plants may suffer from diseases because of low
temperature, insufficient light, chemical residues
and insects, pets, or bacterial diseases.
Almost 90% of the plant's diseases can be identified
through the nature of the leaves such as
color fading, bullheads, limp neck, blackening
of rose petals, pale foliage, black spot, powdery
mildew, and downy mildew. However,
manual monitoring of these diseases is a cumbersome
task.
Data collection at regular time intervals: Trivial
methods of rose farming require manual investigation
and collection of data related to the
growth and development of the plant. Collection
of data such as soil moisture, need for fertilizers,
pesticides, or insecticides, humidity, and
July/August 2021
temperature manually affect the accuracy and
precision adversely.
MyGreen: THE PROPOSED NOVEL
IoT-ENABLED GREENHOUSE
Major parameters that influence the proper
growth of rose plants and flowers in a greenhouse
are proper control of environmental temperature,
humidity, soil and environmental
moisture, environment CO2 level, water level,
UV-light density, and free from heavy dew. Along
with these parameters, the visual health monitoring
of leaf and flower, and proper supply of
minerals, fertilizers, and medicines is also equipotent
as they make the plant healthy and productive.
However, monitoring and maintaining
these parameters pose certain challenges as discussed
in the previous Section. To handle such
challenges, these things need to be automated.
For this purpose, we propose an IoT-based
framework as a mechanism of greenhouse rose
farming automation (see Figure 1). This IoT
framework facilitates the rose plants a favorable
growth environment by providing soil monitoring,
auto-optimization of suitable environment,
optimum irrigation, real-time problem diagnosis,
reduced harvest failure, remote controlling and
management, and cutting down in the operation
cost.
The proposed IoT framework consists of following
three parts:
1) Data acquisition system (DAS): A set of sensors
for collecting real-time data from the
greenhouse.
2) Central actuator manager (CAM): A set of
equipment for performing different task of
the greenhouse and is handled by a set
of actuators.
3) Decision support system (DSS): A DSS is used
to monitor and manage the resources.
Data Acquisition System (DAS)
The DAS (see Figure 2) records the data collected
from various sensors, such as humidity,
water level, the intensity of UV light, CO2 level,
pH and EC value, temperature, mist, and nutrient
levels. These data are captured continuously
from the sensors to monitor the environmental
status of the greenhouse. After sensor data
59
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