Internet of Things Based Smart Plant Monitoring System

Sai Rashmi B J

, Sanjana Alladwar

, Sanjana Sulibhavi

, Shree Lakshmi P

and Priyashree S

Dept of Electrical & Electronics Engineering, BNM Institute of Technology, Bengaluru, Karnataka, India

Keywords: Arduino, Dht11 Sensor, GSM (Global System for Mobile Applications), Internet of Things (IoT).

Abstract: The Internet of Things is the process of connecting any physical objects embedded with sensors, electronics,

software, and network connectively, enabling devices to exchange data and be monitored remotely. IoT can

address water scarcity in agriculture by using sensors to measure soil temperature and moisture content along

with humidity, which will help optimize the usage of water and minimize waste. IoT systems help improve

farming efficiency because real-time data is provided, and processes like irrigation can be automated.

Technology minimizes interference between human intervention, improves accuracy, and its economic

benefits have resulted in its being an important apparatus in modern agricultural practices and other crucial

applications.

1 INTRODUCTION

Plants play a crucial role in the food chain and the

ecological cycle, requiring careful monitoring to

ensure optimal growth and health. Automation and

IoT technology are making plant monitoring systems

smarter by providing real-time data on soil moisture

and environmental conditions. IoT-based solutions

enable intelligent decision-making for resource

management, such as water use in plantations. Soil

moisture, humidity, and temperature sensors placed

near plant roots can detect conditions favourable for

growth. The collected data is transmitted to a web

server (cloud) for analysis, enabling smarter, more

reliable planting practices.

Application of IoT in agriculture has several

benefits and addresses serious issues like water

scarcity. In areas characterized by low levels of

rainfall, the realization of the efficient use of water

resources through the application of IoT improves

crop irrigation in real-time. IoT devices, for instance,

are Arduino IDE and NodeMCU, which often process

sensor data. The technologies offer cost-effective

means of solution in home and large-scale farming.

https://orcid.org/0009-0002-1906-0348

https://orcid.org/0009-0002-3614-4068

https://orcid.org/0009-0002-1972-6680

https://orcid.org/0009-0002-4009-4251

https://orcid.org/0000-0003-2284-4776

Further research is still being conducted in order to

evaluate the adverse impacts of IoT systems on

human health and the environment.

2 LITERATURE SURVEY

Caroline El Fiorenza (2018) et.al., have designed a

smart e-agriculture monitoring based on Arduino

using IoT (Fiorenza et al., 2018). The production of

crops varies from place to place, where each crop has

certain condition for its production. The lack of

information about the crop, leads to failure in

production. This proposed system includes the

monitoring platform for agricultural ecosystem using

smart technology. According to its methodology, the

crops are being monitored with the help of Arduino

boards and GSM technology where in the Arduino

boards behave as a microcontroller. The purpose of

this system is to supply water when the farm is dry

during absence of human, it will also monitor the

humidity, salinity of the soil, soil moisture and

temperature also. This work consists of Arduino

Nano with Node MCU sensors like soil moisture and

124

B J, S. R., Alladwar, S., Sulibhavi, S., P, S. L. and S, P.

Internet of Things Based Smart Plant Monitoring System.

DOI: 10.5220/0013598700004639

In Proceedings of the 2nd International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2024), pages 124-129

ISBN: 978-989-758-756-6

Dht11, along with Solenoid valves, relays. With the

help of internet, the control of the system is handled

and the sensors used in the project stores the

parameters in timely manner.

Prachi Kamble (2020) et.al., focuses on the IoT Based

Plant Monitoring System for the parameters such as

humidity sensor, moisture sensor, temperature

sensors placed in root zone of plant (Kamble et al.,

2020). The module includes a gateway unit

(ESP8266) that handles the sensor information and

transmit data to a android application. This

application is developed to measure approximate

values of temperature sensor, humidity sensor and

moisture sensor that was programmed into a micro-

controller to control quantity of water.

Monirul Islam Pavel (2019) et.al have proposed

an IoT enable device which sends environment data

in real-time to the database along with image of plant

leaf to classify diseases using image processing and

multiclass support vector machine (Pavel et al.,

2020). The proposed model describes the image

processing has been implemented to detect and

classify the affected plant disease. In this process, the

work is divided into four parts, which are image

acquisition and preprocessing, segmentation of

affected region, feature extraction, classification

using multi-class support vector machine algorithm.

The data obtained from the Arduino are stored in a

string format. This data is then transferred as string to

Raspberry Pi 3. Further, the data is split and again

stored in array format. During this process, a Uniform

Resource Locator (URL) is created with data server’s

IP address with corresponding database column name

of each sensor and thus the values of sensor are

obtained.

3 PROBLEM STATEMENT

A smart plant monitoring system leveraging Internet

of Things (IoT) technology aims to address the

challenges associated with traditional plant care

methods by providing real-time monitoring and

automated management functionalities. The problem

statement for a smart plant monitoring system

involves designing a solution to efficiently monitor

and manage the health of plants in various

environments. Busy lifestyles or travel can result in

inconsistent plant care, leading to poor growth or plant

loss.

Figure 1: NodeMCU ESP8266 Wi-Fi Module.

4 METHODOLOGY

The purpose of an IoT-based smart plant monitoring

system is to enhance plant care by leveraging

interconnected devices to collect real-time data on

environmental conditions such as soil moisture,

temperature, and light levels. The goal is to enhance

plant growth, minimize resource wastage, and

improve overall agricultural or horticultural practices

through smart plant monitoring. This system aims to

provide automated and efficient monitoring, that

enables user to remotely track plant health, receive

timely alerts, and optimize resource usage for better

growth and sustainability. This system aims to provide

real-time monitoring and analysis of crucial

environmental variables such as soil moisture,

temperature, humidity, light intensity, and nutrient

levels, ensuring optimal growing conditions for plants.

This system enables remote monitoring and control of

plant health parameters from anywhere, at any time,

through a smartphone or computer interface. The goal

is to empower individuals, farmers, and horticulturists

with actionable insights and automated responses to

ensure the well-being and productivity of plants,

leading to improved crop yields, resource

conservation, and sustainable agricultural practices

(Ashton, 2009), 7], (Chen et al., 2013).

5 SYSTEM CONSTRUCTION

The system of IOT based smart Plant monitoring

system is composed of NodeMCU ESP8266 Wi-Fi

Module is as shown in Fig.1. The module facilitates

to monitor parameters, such as moisture, humidity

and temperature.

Internet of Things Based Smart Plant Monitoring System

125

Figure 2: System Construction of Smart Plant Monitoring

System.

5.1 Hardware Components

5.1.1 NodeMCU ESP8266 Wi-Fi

Module

The ESP-12E module shown in Fig. 2, is an upgrade

form of ESP-12, it adds six GPIOs and supports

UART with a 110-460800 bps transfer rate. It has a

micro-USB port, 15-pin headers for power, SPI,

UART, and GPIO, plus flash and reset buttons.

NodeMCU is an open-source IoT board with Lua,

based on the ESP8266 Wi-Fi & SoC (Zhang et al.,

2014).

5.1.2 DHT11 Temperature and Humidity

Sensor

The device DHT11, shown in Fig.3, provides

temperature and relative humidity measurements

with excellent long-term stability due to its

calibration and digital output. It supports reliable

signal transmission over long distances while

maintaining minimal power usage.

Figure 3: DHT11 temperature and humidity Sensor.

5.1.3 Jumper Wires

These wires shown in Fig.4, are used to connect

components on the breadboard to the header pins

placed on Node-MCU. Jumper wires are used to

create temporary electrical connections between

components on a breadboard.

Figure 4: Jumper Wires.

5.1.4 Soil Moisture Sensor

Soil moisture meter shown in Fig.5, along with the

humidity sensor monitors the water level in the lawn's

root zone, ensuring precise irrigation. These

controllers, like evapotranspiration (ET) controllers,

help to reduce water usage.

Figure 5: Soil Moisture Sensor.

It also maintains the turfgrass quality, where the

appearance of the grass is intensified (Chaparro et al.,

2019).

5.1.5 Relay (5V)

The 5V relay, shown in Fig.6, operates with a coil

voltage of DC 5V and has a rated load capacity of 7A

at 250V. It features a single-pole, double-throw

(SPDT) contact configuration, allowing it to switch

between two different outputs. The design includes

five pins, with the increased capacity to handle up to

7A, making it suitable for various switching

applications.

Figure 6: 5V Relay.

5.1.6 Passive Infrared (PIR) Motion Sensor

This PIR sensor shown in Fig.7, detects motion by

sensing infrared radiation from objects like humans

or animals. It passively identifies changes in infrared

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126

energy when something moves within its range,

triggering responses such as activating lights or

alarms. PIR sensors are energy-efficient and widely

used in security systems and home automation. Their

reliability makes them ideal for covering large areas

(Motlagh et al., 2021), (Tubaishat and Madria, 2022).

Figure 7: PIR Motion sensor.

5.2 Software Components

Blynk, Fig.8, is a platform that enables developers to

build IoT applications for controlling and monitoring

connected devices using a simple drag-and-drop

interface mechanism.

Figure 8: BlynkApp.

Users can design their own mobile app interfaces by

selecting from a wide range of widgets such as

buttons, sliders, graphs, and displays. These

interfaces are then linked to physical hardware

devices like microcontrollers. The Arduino Integrated

Development Environment (IDE), Fig.9, is an open-

source software application that provides a platform

for writing, compiling, and uploading code to

Arduino-compatible microcontroller boards. It offers

a user-friendly interface, and a set of tools designed

to simplify the process of programming Arduino-

based projects. Key features of the Arduino IDE

include Code Editor, Compilation and upload, Serial

monitor.

Figure 9: Arduino IDE.

6 WORKED CARRIED OUT

The circuit connections of IOT Based Smart Plant

Monitoring System using the hardware components

are as shown in Fig.10. The Fig.11, shows the Blynk

software connection used to display the values of

temperature, humidity & Soil moisture. The Fig.12

indicates the Blynk connection when PIR Motion

sensor is in ON state. Fig.13 shows the Blynk

notifications through mobile. The Blynk App display

for Temperature, Humidity and Soil moisture with

PIR sensor in ON state is shown in Fig. 14.

Figure: 10 Circuit Connection.

Figure 11: Blynk Software Display.

Figure 12: Blynk connection display for PIR motion sensor

in ON state.

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127

Figure 13: Blynk Notification through mobile.

Figure 14: Blynk App display for Temperature, Humidity

and Soil moisture with PIR sensor in ON state.

7 RESULTS

The IoT-based Smart Plant Monitoring System has

yielded promising results in revolutionizing the way

we care for our plants. By integrating sensors,

wireless communication, and data analytics, this

system provides real-time monitoring of crucial plant

parameters such as soil moisture, temperature, light

intensity, and humidity. The continuous data

collection and analysis enable precise adjustments to

watering schedules, environmental conditions, and

nutrient levels, optimizing plant growth and health.

Moreover, the system offers remote access through

mobile applications or web interfaces, empowering

users to monitor their plants from anywhere at any

time. IoT-based Smart Plant Monitoring Systems

hold great potential in promoting sustainable

agriculture practices and enhancing green spaces in

both urban and rural settings.

8 CONCLUSIONS

By connecting various soil parameters to the cloud

and enabling remote control via a mobile application,

the Internet of Things-based Smart Garden system

has been proven to function satisfactorily. The system

is designed to monitor sensor data, including

moisture, humidity, temperature, as well as to actuate

other parameters based on requirements. For instance,

if the tank's water level drops to a minimum, the

motor switch will automatically turn on until the

tank's water level reaches its maximum value. This

system can be installed anywhere because of its low

initial cost and ease of installation. The advancement

of sensor technology allows the system to be

upgraded to the next level, allowing users to make the

most economical use of their investment. This

approach reduces labor costs and makes effective use

of the available water resources, which increases

revenue. The system's feedback will help the

gardening process be implemented more effectively.

REFERENCES

M. Mancuso and F. Bustaﬀa (2006), “A Wireless Sensors

Network for Monitoring Environmental Variables in a

Tomato Greenhouse”, IEEE International Workshop on

Factory Communication Systems.

Teemu Ahonen, Reino Virrankoski and Mohammed

Elmusrati , (2008), “Greenhouse Monitoring with

Wireless Sensor Network”. University of Vaasa,

IEEE/ASME.

Caroline El Fiorenza, Sushmita Sharma, Soumya Ranjan,

Shashank, (2018) “Smart e-Agriculture Monitoring

Based on Arduino Using IoT”, International Journal of

Scientific Development and Research, IJSDR.

Prachi Kamble, Sudhanshu Bhagat, Sohail Shaikh, Ronak

Sahu, Chavan, Prajakt Zodge, (2020) “IoT Based

Plant.Monitoring System”, International Journal of

Interdisciplinary Innovative Research & Development

(IJIIRD), ISSN: 2456-236

Monirul Islam Pavel, Sadman Sakib Hasan, Syed

Mohammad Kamruzzaman and Saifur Rahman Sabuj ,

(2019), “An IoT Based Plant Health Monitoring System

Implementing Image Processing”, IEEE 4th

International Conference on Computer and

Communication Systems, Singapore.

Kevin Ashton, (2009), “That Internet of Things thing”,

RFID Journal.

Nikkila, R., Seilonen, I., Koskinen, K., (2010)‘‘Software

Architecture for Farm Management Information

Systems in Precision Agriculture.’’ Comput. Electron.

Agric.

Chen, Joy Iong Zong, Yuan-Chen Chen, and Shien-Dou

Chung, (2013), “Implementation of a Greenhouse Crop

Remote Monitoring System with IOT Technology,

TANET.

Zhang, Xiang Wen, Ran Chen, and Chun Wang, (2014),

“Design for Smart Monitoring and Control System of

Wind Power Plants.” Advanced Materials Research.

ISPES 2024 - International Conference on Intelligent and Sustainable Power and Energy Systems

128

D. Chaparro, MerceVall-llossera, M. Piles, A. Camps, C.

R¨udiger and R. Riera-Tatch, (2019), “Predicting the

Extent of Wildfires using Remotely Sensed Soil

Moisture and Temperature Trends”, IEEE Journal of

Selected Topics in Applied Earth Observations and

Remote Sensing.

N. H. Motlagh et al., (2021), “Monitoring social distancing

in smart spaces using infrastructure-based sensors”

Proc. IEEE World Forum Internet Things (WF-IoT).

Malik Tubaishat, Sanjay Kumar Madria, (2022) “Sensor

networks: An Overview”, IEEE Potentials 05/2013.PV

systems,” Simulation Modelling Practice and Theory.

Internet of Things Based Smart Plant Monitoring System

129