IOT-based Design and Simulation of Smart Greenhouse Monitoring and Control System

Abstract

In recent years, "smart agriculture" has emerged as a promising strategy for enhancing the efficiency and longevity
of contemporary farming. This article details the planning and modeling of an Internet of Things (IoT) smart
greenhouse management and monitoring system using MATLAB. In real time, the system tracks five important
environmental variables using modelled sensor readings: soil moisture, humidity, light intensity, CO₂ concentration,
and temperature. For the purpose of environmental monitoring and management, we have established precise cutoff
values for each metric. When a value above its threshold, an alarm is sent out and appropriate procedures, such as
the activation of fans, water pumps, and artificial lighting, are immediately initiated. The system ensured the
correctness of the projected findings under various environmental circumstances by testing this configuration using
a dataset of 100 time-series samples. The simulation found that temperature was the most unpredictable factor,
leading to 58 warnings. Then came 52 warnings about soil moisture and 46 about humidity. Only 29 and 17 alarms,
respectively, were generated by CO₂ levels and light intensity, which were closer to their ideal limits. In response to
any alarm, the system automatically handles the inappropriate circumstances based on sensor input. The model made
use of graphs and pie charts to examine the system. This study lays the groundwork for an Internet of Things (IoT)
smart greenhouse system that may boost efficiency and longevity in real time. Assisting small farmers and
promoting sustainable agriculture is the primary goal of this project.
Smart farming, automation, environmental monitoring, control systems, sensor data, the internet of things, and
MATLAB simulation are all related terms.