<p>There is a growing demand for
indoor farm management systems that can track plant growth, allow automatic
control and aid in real-time decision making. Internet of Thing (IoT)-based
solutions are being applied to meet these needs and numerous researchers have
created prototypes for meeting specific needs using sensors, algorithms, and
automations. However, limited studies are available that report on comprehensive
large-scale experiments to test various aspects related to availability, scalability
and reliability of sensors and actuators used in low-cost indoor farms. The
purpose of this study was to develop a low-cost, IoT devices driven indoor farm
as a testbed for growing microgreens and other experimental crops. The testbed
was designed using off-the-shelf sensors and actuators for conducting research experiments,
addressing identified challenges, and utilizing remotely acquired data for developing
an intelligent farm management system. The sensors were used for collecting and
monitoring electrical conductivity (EC), pH and dissolved oxygen (DO) levels of
the nutrient solution, light intensity, environmental variables, and imagery
data. The control of light emitting diodes (LEDs), irrigation pumps, and camera
modules was carried out using commercially available components. All the
sensors and actuators were remotely monitored, controlled, and coordinated
using a cloud-based dashboard, Raspberry Pis, and Arduino microcontrollers. To
implement a reliable, real-time control of actuators, edge computing was used
as it helped in minimizing latency and identifying anomalies.</p>
<p>Decision
making about overall system performance and harvesting schedule was accomplished
by providing alerts on anomalies in the sensors and actuators and through installation
of cameras to predict yield of microgreens, respectively. A split-plot
statistical design was used to evaluate the effect of lighting, nutrition
solution concentration, seed density, and day of harvest on the growth of
microgreens. This study complements and expands past efforts by other
researchers on building a low cost IoT-based indoor farm. While the experience
with the testbed demonstrates its real-world potential of conducting experimental
research, some major lessons were learnt along the way that could be used for
future enhancements.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/15085230 |
| Date | 30 July 2021 |
| Creators | Madhu Lekha Guntaka (11211111) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/IOT_BASED_LOW-COST_PRECISION_INDOOR_FARMING/15085230 |
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