Group Number: A32

MINI PROJECT REPORT ON

“IOT BASED PLANT MONITORING SYSTEM USING

NODEMCU”

SUBMITTED TO SAVITRIBAI PHULE PUNE UNIVERSITY, PUNE

IN THE FULFILLMENT OF THE REQUIREMENTS
FOR THE COMPLETION OF MINI PROJECT

OF

THIRD YEAR ENGINEERING

IN
ELECTRONICS & TELECOMMUNICATION
BY

SAKSHI GOSAVI Exam No. T1902303111

SONALI BANKAR Exam No. T1902303024
SHRUTIKA PATANKAR Exam No. T1902303248
UNDER THE GUIDANCE OF

Dr. T.V.KAFRE

DEPARTMENT OF ELECTRONICS & TELECOMMUNICATION ENGINEERING

SINHGAD COLLEGE OF ENGINEERING
S. No. 44/1, OFF SINHGAD ROAD, VADGAON BK, PUNE – 411041

APRIL 2025
 (2024-25)

CERTIFICATE
This is to certify that the Mini Project entitled

“IOT BASED PLANT MONITORING SYSTEM USING NODEMCU”

Submitted By
SAKSHI GOSAVI
SONALI BANKAR
SHRUTIKA PATANKAR

is a bonafide work carried out by them under the supervision of Dr.T.V.KAFRE and it
is approved for the partial fulfillment of the requirements of T.E. E&TC Engineering
submitted to Savitribai Phule Pune University, Pune.

The Mini Project work has not been earlier submitted to any other institute or university
for the award of degree or diploma.

Dr. T.V.KAFRE Dr. D.GANGE Dr. M. B. Mali Dr. S. D. Lokhande

Guide Mini Project Coordinator Head Principal
Department of E&TC Department of E&TC Department of E&TC SCOE, Pune

Place: Pune

Date:
 ACKNOWLEDGEMENT

We are feeling very humble in expressing my gratitude. It will be unfair to bind the
precious help and support which we got from many people in few words. But words are the
only media of expressing one’s feelings and my feeling of gratitude is absolutely beyond these
words. It would be my pride to take this opportunity to say the thanks.

Firstly, we would thank our beloved guide Dr. T.V.KAFRE for his valuable guidance,
patience and support; He was always there to force us a bit forward to get the work done
properly and on time. He has always given us freedom to do mini project work and the chance
to work under his supervision.

We would like to express our sincere thanks to Dr. D.GANGE, mini project
coordinator, Department of E&TC, for his constant encouragement in the fulfillment of the
mini project work. We would also like to express our sincere thanks to Dr. M. B. Mali, Head,
Department of E&TC for his co-operation and useful suggestions. We would also like to thank
Dr. S. D. Lokhande, Principal, Sinhgad College of Engineering. He always remains a source
of inspiration for us to work hard and dedicatedly.
It is the love and blessings of our families and friends which drove us to complete this
project work.

Thank you all!

SAKSHI GOSAVI
SONALI BANKAR
SHRUTIKA PATANKAR
 ABSTRACT
This project presents the development of an IoT-based Plant Monitoring System designed to
automate environmental data acquisition and irrigation control for enhanced plant health
management. The system integrates a microcontroller unit (e.g., ESP32/Arduino) with a suite
of sensors including soil moisture sensors, DHT11/DHT22 for temperature and humidity, and
a light-dependent resistor (LDR) for light intensity detection. Sensor data is collected at regular
intervals and transmitted via Wi-Fi to a cloud platform such as ThingSpeak, Firebase, or Blynk,
enabling real-time remote monitoring through a web or mobile dashboard.

The system employs conditional logic to initiate automated irrigation using a relay-controlled
water pump when soil moisture falls below a defined threshold. Data analytics features provide
trend visualization and historical data logging for predictive insights. The system demonstrates
high reliability, low latency, and minimal power consumption, making it suitable for
applications in smart agriculture, greenhouse automation, and urban gardening. This IoT-based
approach not only supports efficient plant management but also promotes sustainable practices
in agriculture and home gardening. The proposed system demonstrates a scalable and cost-
effective solution for modern smart farming applications.
 CONTENTS

Chapter Description Page No.

1 INTODUCTION 1

1.1 Introduction of the Project 1

1.2 Aim and objectives of the Project 2
1.3 Hardware and Software Platform Used 3
1.4 Advantages and Applications 4

2 LITERATURE REVIEW 5
2.1 Introduction (Recent trends of work / State of Art systems) 5
2.2 Literature Survey (Min. 5 references) 6
2.3 Description of Major System Components 7

3 DESIGN AND DEVELOPMENT 10

3.1 Block Diagram and Description 10
3.2 Circuit design (Circuit schematic) and Description 11
3.3 Software Design Steps (Algorithm / Flowcharts explanations) 14
3.4 PCB Artwork Design 17

4 RESULT AND DISCUSSIONS 18

4.1 Graphical Form of the Results and its Description 18
4.2 Tabular Form of the Results and its Description 19

5 CONCLUSIONS & FUTURE SCOPE 20

5.1 Conclusions based on Overall Mini Project 20
5.2 Future Scope 20

6 REFERENCES 21
DATASHEETS (Specific pages of Major Components only) 22
 Chapter 1

Introduction

1.1 Introduction of the project:

In recent years, the Internet of Things (IoT) has emerged as a powerful technology for
automating and optimizing various aspects of everyday life. One such promising application
is in the field of agriculture and home gardening, where IoT can significantly enhance plant
care and monitoring.

Traditional plant monitoring requires constant human attention, which may not always be
feasible, especially in busy urban lifestyles or large-scale farming. Factors such as irregular
watering, fluctuating temperatures, and poor soil conditions can adversely affect plant
health. This creates the need for a smart, autonomous system that can monitor
environmental conditions and notify users when intervention is needed.

In this project, we will learn about the IoT Based Smart Agriculture & Automatic Irrigation
System with Nodemcu ESP8266. The NodeMCU collects data from various sensors and
transmits it to a cloud platform or mobile application, enabling users to monitor the condition
of their plants remotely. With the integration of IoT, the system can also send alerts or
recommendations when certain conditions go beyond preset thresholds, thereby assisting
users in taking timely actions to ensure healthy plant growth.

By automating the monitoring process, this system not only reduces the manual effort involved
in plant care but also contributes to water conservation and improved yield, making it
particularly beneficial for urban gardening, smart farming, and educational purposes.

Agriculture plays a vital been always hindering the development of our country. Consequently,
the only solution to this problem is smart agriculture by modernizing the current traditional
method of agriculture. The internet of things (IoT) enables various applications of crop growth
monitoring and selection, automatic irrigation decision support, etc We proposed the ESP8266
IoT role in the development of agricultural countries. Some issues concerning agriculture have
automatic irrigation system to modernize and improve the productivity of crop.

1
1.2 Aim and Objectives of the Project:

Aim:

To design and develop an IoT-based plant monitoring system that enables real-time monitoring of
environmental parameters such as soil moisture, temperature, humidity, and light intensity to enhance
plant health and support smart agriculture practices.

IoT plant monitoring systems can help farmers optimize resource allocation, such as labor, equipment,
and inputs, by providing data-driven insights.

By monitoring soil moisture, temperature, and other environmental factors, system can help to reduce
water and chemical waste.

Objectives:

To design and develop a smart plant monitoring system using NodeMCU (ESP8266) as
the central controller for data collection and transmission.

To integrate multiple environmental sensors, including soil moisture, temperature, and

humidity sensors, to monitor plant health parameters in real-time.

To enable wireless data transmission using the built-in Wi-Fi capabilities of NodeMCU,
ensuring remote accessibility of sensor data via a cloud platform or mobile application.

To implement real-time monitoring and alert notifications, so users can take immediate
action when environmental conditions fall outside optimal ranges.

To provide a user-friendly interface (e.g., Blynk, ThingSpeak, or custom dashboard) for

visualizing sensor data and monitoring trends over time.

To reduce manual effort and water usage by potentially integrating an automated irrigation
system triggered by soil moisture levels.

To promote sustainable and smart gardening practices using IoT technology, with
applications in both domestic and agricultural settings.

2
1.3 HARDWARE AND SOFTWARE PLATFORM USED:

Hardware Components:

1.NodeMCU (ESP8266)
Acts as the main microcontroller with built-in Wi-Fi for data transmission.
2.Soil Moisture Sensor
Measures the moisture content in the soil to detect dryness or overwatering.
3.DHT11 / DHT22 Sensor
Measures ambient temperature and humidity levels around the plant.
4.Light Sensor
Measures the intensity of light to check sunlight availability for the plant.
5.Water Pump
Used for automated irrigation if soil moisture falls below a threshold.
6.Relay Module
Controls the water pump or other actuators based on sensor readings.
7.Jumper Wires
For connecting sensors and components to the NodeMCU.

Software Requirements:

1.Arduino IDE
Version: 1.8.19
Used for writing and uploading code to the NodeMCU.
2.Blynk App
Version: 3.1.2
Cloud platform or mobile interface for real-time data monitoring and control.
3.ESP8266 Board Package
Installed in the Arduino IDE to support NodeMCU programming.
4.Libraries Required:
ESP8266WiFi.h – for Wi-Fi functionality
DHT.h – for the DHT11/DHT22 sensor

3
1.4 Advantages & Applications:

Advantages:
1.Real-time Monitoring:
Constant observation of plant health and environmental conditions allows timely
intervention.

2.Water Conservation:
Automated alerts on soil moisture help prevent over-watering and support sustainable water
usage.

3.Remote Access:
Users can monitor plant status from anywhere using mobile or web platforms, reducing the
need for physical presence.

4.Increased Crop Yield & Plant Health:

Timely care based on accurate data leads to healthier plants and potentially higher yields.

5Low Maintenance:
Once set up, the system runs with minimal manual effort, especially if integrated with
automated watering.

Applications:

1.Smart Home Gardening:

Ideal for urban gardeners to take care of indoor or balcony plants.

2.Greenhouses:
Ensures optimal growing conditions and reduces labour-intensive monitoring.

3.Agriculture and Farming:

Used in large-scale farms for precision agriculture and better crop management.

4.Research and Education:

Helpful for agricultural studies, plant biology research, and as an educational project for
students.

5.Botanical Gardens & Nurseries:

Maintains plant health across large collections efficiently.

4
 Chapter 2

LITERATURE REVIEW

2.1 Introduction (Recent trends of work / State of Art systems)

The integration of the Internet of Things (IoT) in agriculture and plant monitoring has
emerged as a key driver in advancing precision farming and smart gardening. With the global
push towards sustainability, resource optimization, and automation, IoT-based systems are
being increasingly deployed to monitor environmental parameters that directly influence
plant health and productivity.

Recent trends in this field highlight the use of low-cost, energy-efficient sensors and wireless
microcontrollers (such as NodeMCU, ESP8266, or ESP32) to collect data on soil moisture,
temperature, humidity, and light intensity. This data is transmitted in real-time to cloud-based
platforms like ThingSpeak, Blynk, or Firebase, allowing users to access and analyse it
remotely through mobile or web applications.

Furthermore, machine learning algorithms are now being explored to predict plant diseases or
optimize irrigation schedules based on historical data trends. Integration with automated
irrigation systems is also becoming more common, enabling fully autonomous plant care with
minimal human intervention.

State-of-the-art systems incorporate not only basic sensing but also data analytics,
visualization tools, and alert systems. For example, some systems trigger notifications or
even activate watering pumps automatically when the soil moisture drops below a threshold.
These advancements are geared toward reducing human effort, conserving resources, and
increasing agricultural productivity, especially in water-scarce regions.

Despite the progress, challenges remain in terms of scalability, data security, network
reliability, and affordable deployment in remote or underdeveloped areas. However, ongoing
research and innovation continue to make these systems more accessible, efficient, and
robust.

5
2.2 Literature Survey

In recent years, the integration of Internet of Things (IoT) technology into agriculture has led
to the development of numerous smart systems aimed at improving plant monitoring and
irrigation efficiency. The literature reviewed below highlights the trends, methodologies, and
technologies used in similar systems.

1.Smart irrigation System using IoT

A study by Patel et al. (2018) proposed an automated irrigation system using Arduino and soil
moisture sensors. Their system automatically watered plants when the moisture level fell below
a set threshold. However, it lacked remote monitoring capabilities and was not integrated with
a Wi-Fi-based platform, which limits its real-time data accessibility.

2.Wireless plant Monitoring using Raspberry Pi

In a project by Sharma and Gupta (2019), Raspberry Pi was used to collect data from sensors
and upload it to a web interface. Although the system was efficient, the cost and complexity of
Raspberry Pi made it less suitable for small-scale or low-budget applications. NodeMCU offers
a more cost-effective and simpler alternative.

3. IoT smart garden monitoring system

Khan et al. (2020) implemented a plant monitoring system using NodeMCU, DHT11, and soil
moisture sensors, with data uploaded to ThingSpeak. Their work demonstrated the feasibility
of real-time environmental monitoring using cloud platforms. However, their project was
limited to monitoring only, without implementing automatic irrigation or alert mechanisms.

4.Blynk based Iot gardening system

A practical project published on various open-source platforms like Hackster.io shows the use
of NodeMCU with Blynk to display real-time data and receive notifications. These DIY
systems proved the usability of Blynk for mobile integration but often lacked detailed sensor
calibration or scalability for larger systems.

6
2.3 Description of Major System Components:

1.Node MCU (ESP8266) WIFI Module:

Fig: Node MCU (ESP8266)

NodeMCU is an advanced API for hardware input/output device which can be dramatically
reduces the work for configuring manipulative hardware. It uses a code like Arduino but rather
is an interactive script called Lua. It is an open source IoT platform. It runs on a firmware of
ESP8266 Wi-Fi Soc produced by Espressif systems. NodeMCU has 16 input/output pins and
hence 16 nodes can be connected to a single node. The ESP8266 is Wi-Fi Soc which is
integrated with a Ten silica Xtensa LX106 core which is widely used in IoT applications.”
NodeMCU” refers in default to the firmware rather than the development kits. ESP8266 is an
inbuilt WiFi module which can also be used an individual module as a Wifi module.

2. 5V Water Pump:

Fig: 5V Water Pump

DC 5V Mini Submersible Noiseless Water Pump is a low-cost, small size Submersible Pump. It can
take up to 150 Liters per hour with a very low current consumption from 300mA to 1A max. The
water pump works using water suction method which drain the water through its inlet and released it
through the outlet.

7
3. Soil Moisture Sensor:

Fig: Capacitive Soil Moisture Sensor V1.2

Soil moisture sensors measure the volumetric water content in soil. The direct gravimetric
measurement of free-soil moisture requires removing, drying and weighing of a sample, soil
moisture sensors measure the volumetric water content indirectly by using some other property
of the soil, such as electrical resistance, dielectric constant, or interaction with neutrons, as a
proxy for the moisture content. The relation between the measured property and soil moisture
must be calibrated and may vary depending on environmental factors such as soil type,
temperature, or electric conductivity. Reflected microwave radiation is affected by the soil
moisture and is used for remote sensing in hydrology and agriculture. Portable probe
instruments can be used by farmers or gardeners. Soil moisture sensors typically refer to
sensors that estimate volumetric water content. Another class of sensors measure another
property of moisture in soils called water potential; these sensors are usually referred to as soil
water potential sensors and include tensiometers and gypsum blocks.

4. DHT11 Humidity Temperature Sensor:

Fig: 5V Relay Module

The DHT11 is a basic, ultra low-cost digital temperature and humidity sensor. It uses a capacitive
humidity sensor and a thermistor to measure the surrounding air, and spits out a digital signal on the
data pin (no analog input pins needed). This sensor can be easily interfaced with any micro-controller
such as Arduino, Raspberry Pi etc.… to measure humidity and temperature instantaneously. DHT11
sensor consists of a capacitive humidity sensing element and a thermistor for sensing temperature. The
humidity sensing Capacitor has two electrodes with a moisture holding substrate as a dielectric between

8
them. Change in the capacitance value occurs with the change in humidity levels. The IC measure,
process this changed resistance values and change them into digital form.

5. Jumper Wires

In this project, jumper wires are used to establish electrical connections between the
NodeMCU, sensors, relay module, and breadboard. These are essential for connecting
input/output pins and powering the components.

Types of Jumper Wires Used:

1.Male-to-Male (M-M)

Used to connect NodeMCU pins to a breadboard, or to connect between components on the

breadboard.

2.Male-to-Female (M-F)

Used to connect sensor modules or relay modules (which often have male pins) directly to
the NodeMCU female headers.

6. LCD

The term LCD stands for liquid crystal display. These displays are mainly preferred for
multi-segment light-emitting diodes and seven segments. The main benefits of using this
module are inexpensive; simply programmable, animations, and there are no
limitations for displaying custom characters, special and even animations, etc.

9
 Chapter 3

Design and Development

3.1 Block Diagram and Description

Block Diagram :

Description:

The Physical Description of project can be represented by the above Fig 5. All Sensors are
connected to the NodeMCU and DC Pump and Relay module is connected to Power Supply.
Here we use the power supply as Battery. The Output can be shown in Blynk App. This app
is used to Monitor and Control our Hardware project and display the parameters in Web
Dashboard of Blynk App. The circuit Diagram can be shown in below Figure:6 The
connections of circuit are explain below. In NodeMCU we use D3, D2, D5 and A0 along
with VCC and GND Pins.DTH11 Sensor consist of Three pins the data pin is connected to
D3 of MCU and Supply and Ground pin is connected to VCC and GND respectively. Soil
moisture sensor signal pin is connected to A0 and remaining two pins, one is connected to
supply and another is ground. LED positive is connected to D2 whereas negative is
grounded. Relay Module data pin is connected to the D5 and Supply and Ground is

10
 connected to VCC and GND Respectively. DC Pump Relay Module is connected to the
Battery. DC pump Operates based on the Relay and Battery. When we give Power Supply
to NodeMCU 5V or 9V then the user program in flash memory is enables and display the
outputs. According to the displayed information we overcome the Soil Moisture related problems
then we improve the Soil Moisture by giving the proper water supply to plant through motor. Then
Automatically the we improve plant growth and also reduce the wastage of water. When moisture
level is high then the motor is in OFF position.

3.2 Circuit Diagram and Description

Circuit Diagram:

Fig: Circuit Diagram.

➢ Description
Main Components:
1. NodeMCU (ESP8266)
2. Soil Moisture Sensor (FC-28)
3. Relay Module
4. Water Pump
5. DHT11 Sensor (Temperature & Humidity)
6. Power Supply (5V and GND)

11
1.NodeMCU (ESP8266)

• Acts as the brain of the system, reading sensor data and controlling the relay.
• Connected to:
o Soil moisture sensor (Digital pin D2)
o DHT11 sensor (Digital pin D4)
o Relay module (Digital pin D1)

2.Soil Moisture Sensor (FC-28)

• Detects the moisture level of the soil.
• Connected to a small signal amplifier module, which has:
o VCC to 3.3V or 5V (from NodeMCU)
o GND to GND
o DO (Digital Output) to D2 pin on NodeMCU
• When the soil is dry, the DO pin outputs HIGH; when wet, it outputs LOW.

3.DHT11 Sensor
• Measures temperature and humidity.
• Connections:
o VCC to 3.3V or 5V (depending on model)
o GND to GND
o Data pin to D4 on NodeMCU
• Provides environmental data for monitoring.

4.Relay Module
• Used to control the water pump.
• Triggered by digital pin D1 on NodeMCU.
• Relay input pins:
o IN to D1
o VCC to 3.3V or 5V
o GND to GND
• Relay output:
o Controls a separate power circuit for the water pump.

12
5.Water Pump

• Controlled by the relay.

• Turns ON when soil is dry and OFF when soil is wet.
• Powered via the relay using an external 5V supply.

6.Power Supply
• The entire system is powered using a 5V source.
• Common GND is shared between the sensors, NodeMCU, and the relay.
• Be cautious to avoid drawing too much current from NodeMCU's 3.3V pin —
power the pump and relay with an external 5V supply if needed.

Working Summary
1. The soil moisture sensor checks the water level in the soil.
2. If the soil is dry, the NodeMCU activates the relay, turning on the water pump to
irrigate the plant.
3. The DHT11 continuously monitors temperature and humidity, sending the data to
the NodeMCU.
4. All data can be viewed remotely via an IoT platform like Blynk, ThingSpeak, or
Firebase (if programmed accordingly).

13
3.3 Software Design steps (Algorithm /Flowchart explanations)
Software Design Steps

1. Sensor Initialization:

o Initialize communication with the DHT11 sensor and Soil Moisture Sensor.

o Set up pin modes for the relay module and sensors.

2. Wi-Fi Connectivity Setup:

o Configure the NodeMCU to connect to Wi-Fi.

o Optional: Connect to an IoT platform (e.g., ThingSpeak, Blynk, Firebase)

for remote monitoring.

3. Read Sensor Data:

o Read soil moisture from the digital output of the soil sensor.

o Read temperature and humidity from the DHT11 sensor.

4. Decision Making:

o If soil is dry, activate the relay to turn ON the water pump.

o If soil is moist, turn OFF the water pump.

5. Data Upload (optional):

o Send sensor data to a cloud dashboard for real-time monitoring.

6. Notifications/Alerts (optional):

o Send alerts via email, SMS, or mobile notifications if any value crosses a
threshold.

7. Loop and Delay:

o Repeat the process at a defined interval (e.g., every 10 seconds)

14
Algorithm (Step-by-Step)

1. Start

2. Initialize NodeMCU and sensor pins

3. Connect to Wi-Fi network

4. Setup connection to cloud platform (e.g., Blynk or ThingSpeak)

5. Loop:

a. Read soil moisture sensor value

b. Read temperature and humidity from DHT11/DHT22

c. Display/send data to cloud or app

d. If soil moisture < threshold:

i. Send alert or turn on water pump

Else:

i. Keep pump off

e. Wait for a short delay

6. Repeat loop

15
Flowchart

[Start]
|
v
[Initialize NodeMCU and Sensors]
|
v
[Connect to Wi-Fi]
|
v
[Read Soil Moisture, Temp, Humidity]
|
v
[Send Data to Cloud/App]
|
v
[Soil Moisture < Threshold?]
| |
Yes No
| |
v v
[Turn on Pump] [Turn off Pump]
| |
+-------------+
|
v
[Delay/Wait]
|
v
[Loop]

16
3.4 PCB Artwork Design

17
 Chapter 4

RESULT AND DISSCUSSIONS

4.1 Graphical Form of the Results and its Description

Flowchart Description

1. Start – The system begins execution.

2. Initialization – Sensors (Soil Moisture, DHT11) and Wi-Fi are set up and initialized
on the NodeMCU.

3. Read Sensor Data – The program reads current soil moisture status and environmental
data (temperature and humidity).

4. Decision Making – The soil moisture is checked. If the value is below a set threshold
(i.e., the soil is dry), the water pump is turned ON. Otherwise, it remains OFF.

5. Data Upload – The data is optionally sent to a cloud service like ThingSpeak or Blynk
for remote monitoring.

6. Delay – A small delay (e.g., 5–10 seconds) is introduced before the next reading cycle.

7. Loop – The entire process repeats continuously, ensuring real-time monitoring and
control.

4.2 Tabular Form of the Results and its Description

18
4.3 Concluding Remark on Results

• The system effectively monitored the soil condition and responded by activating the
water pump when the soil was dry.

• As seen at 09:00 AM and 09:30 AM, when the soil moisture was detected as "Dry",
the system turned ON the pump to irrigate the plant.

• Once the soil returned to a "Moist" condition, the pump was automatically turned
OFF, showing the responsiveness and accuracy of the setup.

• Temperature and humidity readings were stable throughout the testing period,
proving the functionality of the DHT11 sensor.

• These results validate that the system is suitable for autonomous plant care, reducing
the need for manual watering and ensuring consistent soil moisture.

19
 Chapter 5

CONCLUSIONS & FUTURE SCOPE

5.1 Conclusion
In this project, we implemented an automatic irrigation facility which one can easily control
from their home by using a simple online application. Labor work would be eliminated and
we would get accurate results. The proposed system can reduce the efforts of farmers and
provides a high yield. It also conserves water for irrigation by locating the sensor at the right
position above the soil level. This work has shown that plants can still sustain at low moisture
level when the temperature is moderate. Analysing more than one parameter has made this
system an efficient one for managing the field.

5.2Future Scope
The Future Scope of this Project never be ended Because in today fast World every person
will Require a helping hand to take care of plant and Plant health status. This is Further used
for large Scale of Agriculture Purpose to increase the Crop Rate and help farmers to reduce
man power.

Machine results and sensing provide accurate results which will help optimize production.

With IOT the Plant Monitoring system can be made portable.

Plant Monitoring system can be set up in extreme climatic conditions as the automated
system will continuously make alterations such that suitable conditions for the plants are
sustained.

20
 REFRENCES
[1] Abhishek Gupta, Shailesh Kumawat, Shubham Garg, "Automated Plant Watering System", Vol-2,
Issue-4, 2016 ISSN: 2454 - 1362.

[2] Taylor Francis Group, "Automated Plant Watering System", LLC, pp.59-69, 16 September
2016.Taylor Francis Group, “Automated Plant Watering System", LLC, pp.59-69, 16 September 2016.

[3] T.Thamaraimanalan , S.P.Vivekk ,G.Satheeshkumar, P.Saravanan," Smart Garden Monitoring

System Using IOT",IEEE,pp.5-10,2018.

[4] Arul Jai Singh, Raviram, Shanthosh Kumar, "Embedded Based Green House Monitoring system
using pic Microcontroller", IEEE Trans. Syst, Man, Cybern. Systems and Humans, vol. 41, no. 6,
pp.1064-1076, November 2011.

21
 DATASHEETSS

ESP8266 Datasheet

Manufacturer: Espressif Systems

Model: ESP8266EX (commonly seen in ESP-01, ESP-12, boards, etc.)

Key Features:

Wi-Fi Standards: 802.11 b/g/n (2.4 GHz)

CPU: 32-bit Tensilica L106 @ 80/160 MHz

Flash Memory: External (512 KB to 4 MB depending on the module)

RAM: ~50 KB usable

Operating Voltage: 3.0V - 3.6V (3.3V typical)

I/O Voltage Tolerance: 3.3V (not 5V tolerant)

GPIO Pins: Up to 17 GPIOs (depends on the module)

Communication Interfaces:

UART

SPI

I2C (software)

PWM

22
ADC (10-bit, 1 channel)

Power Consumption:

Active Mode: ~70-200 mA (during transmission)

Sleep Mode: ~20 µA (Deep Sleep)

Wi-Fi Capabilities:

Station (STA) / Soft Access Point (AP) / Both

Integrated TCP/IP stack

WEP/WPA/WPA2 security

Common Use Cases:

IoT projects

Wireless data logging

Home automation

Smart devices

Development Support:

Programming via Arduino IDE, Micro Python, or AT Commands

Compatible with popular platforms like NodeMCU, Wemos D1 Mini

23