Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology

ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

Ragi Pest Control

Sharanesh Prabhu Upase1 Nikhil2
Computer Science and Engineering Computer Science and Engineering
Dayananda Sagar University Bengaluru, India Dayananda Sagar University Bengaluru,India

Rakesh G S3 Chandru R4
Computer Science and Engineering Computer Science and Engineering
Dayanaanda Sagar University Bengaluru, India Dayananda Sagar University Bengaluru,India

Vedashree L V5 (Assistant Professor)

Computer Science and Engineering
Dayananda Sagar University Bengaluru,India

Abstract:- The rise of global population has put reduce the use of harmful chemicals in agriculture and
increasing pressure on the agriculture industry to meet improve crop yield while ensuring sustainable and
the demand for food. However, the growing use of environmentally friendly practices.
pesticides and insecticides in conventional farming
practices has caused significant harm to the environment Keywords:- Arduino, Programming, Pest Control.
and human health. Thus, there is a growing interest in
using sustainable agriculture practices that reduce the use I. INTRODUCTION
of these harmful chemicals. One such practice is pest
detection, which enables farmers to detect pests in their Agriculture is a vital industry that feeds the world's
crops before they cause significant damage. In this population. However, crop pests can cause significant damage
context, this project aims to develop a pest detection to crops, leading to lower yields and economic losses for
system using IoT and Arduino. The system will be farmers. Traditional pest monitoring methods involve manual
designed to detect pests in crops through a combination inspection of crops, which can be time-consuming and
of sensors and machine learning algorithms. The system inefficient. In recent years, there has been a growing interest
will consist of an Arduino microcontroller, soil moisture in using Internet of Things (IoT) technology to develop smart
sensors, temperature and humidity sensors, infrared agriculture systems that can automate the pest monitoring
sensors or camera modules, and a Wi-Fi or Bluetooth process. One such system is a pest detection system using IoT
module. The sensors will collect data on soil moisture and Arduino.
levels, temperature, humidity, and pest activity. The data
will be sent to a cloud-based server or database for The system uses sensors to monitor the environment in
analysis and visualization. The infrared sensor or camera which crops are growing, such as temperature, humidity, and
module will detect the presence of pests in the crops. The soil moisture. This data is sent to a cloud-based server or
system will use machine learning algorithms to database, where it is analysed and used to detect anomalies or
distinguish between pests and other objects, such as signs of pest damage. In addition, the system can use infrared
leaves or debris. When pests are detected, the system will sensors or camera modules to directly detect pests or pest
alert the farmer through a buzzer or LED connected to damage on the crops. Once pests are detected, the system
the Arduino board. The farmer can then take appropriate alerts the farmer through a buzzer or LED connected to the
action, such as applying pesticide or removing infested Arduino board.
plants. The pest detection system has the potential to
reduce the use of harmful pesticides and insecticides in This allows the farmer to take quick action to prevent
agriculture, as farmers will be able to identify pests further damage to the crops, such as applying pesticide or
before they cause significant damage. The system will also removing infested plants. The system cans also track and store
provide farmers with real-time information on pest pest detection data over time, providing valuable insights into
activity, enabling them to take proactive measures to pest trends and patterns.
control pests and reduce crop damage. Additionally, the
system can track and store the pest detection data over Overall, the pest detection system using IoT and
time, allowing farmers to monitor trends and patterns in Arduino offers a cost-effective and efficient solution to pest
pest activity. In conclusion, this project proposes the monitoring in agriculture. By automating the pest monitoring
development of a pest detection system using IoT and process, farmers can save time and money while protecting
Arduino that will enable farmers to monitor pest activity their crops from pests.
in their crops in real-time. The system has the potential to

IJISRT24APR830 www.ijisrt.com 1172

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

A. Objectives B. Hardware Components

 Early Detection of Pest Infestations:  Soil Moisture Sensor Module Pinout Configuration
The system should be able to detect pests early on before
they can cause significant damage to crops, allowing farmers
to take proactive measures to control the pests and minimize
crop damage.

 Real-Time Monitoring:
The system should provide real-time monitoring of crop
health and pest activity, allowing farmers to respond quickly
to any issues that arise.

 Improved Accuracy:
The use of IoT sensors and data analysis can provide
more accurate and detailed information on crop health and
pest activity than traditional monitoring methods.

 Cost-Effective:
The system should be cost-effective and easy to
implement, allowing farmers to adopt the technology without
significant financial investment. Fig 1 Soil Moisture Pinout

 Environmentally Friendly:  Arduino Board:

The system should minimize the use of harmful The most common board for IoT projects is the Arduino
pesticides and other chemicals, helping to reduce the Uno, but other boards like Arduino Mega or Node MCU can
environmental impact of agriculture. also be used.

 Remote Access:  Soil Moisture Sensor:

The system should allow farmers to remotely monitor This sensor is used to measure the moisture content of
their crops and receive alerts on their mobile devices or the soil around the plants. If the soil is too wet, it can lead to
computers, allowing them to take action even when they are root rot, and if it is too dry, it can cause the plant to wilt.
not on-site.
 Soil Moisture Sensor Module Features & Specifications
 Data Analysis:
The system should be able to collect and analyze data
over time, allowing farmers to identify trends and patterns in
pest activity and crop health. This can help them make more
informed decisions and optimize their farming practices.

A pest detection system using IoT and Arduino is an

automated system designed to detect the presence of pests in
crops and alert farmers to potential pest infestations. The
system uses IoT sensors to monitor environmental conditions
such as soil moisture, temperature, and humidity and sends
data to a cloud-based server or database. Additionally, an
infrared sensor or camera module is used to detect pests or
signs of pest damage in crops. If pests are detected, the
system alerts the farmer through a buzzer or LED connected
to the Arduino board.
Fig 2 Soil Moisture Specifications
This system is highly beneficial for farmers as it helps
to identify pests early, allowing for proactive measures to be  Temperature and Humidity Sensor:
taken to control pest infestations and reduce crop damage. By This sensor measures the temperature and humidity
using IoT sensors and cloud-based data storage, the system levels in the environment. This information can be used to
can provide real-time data and enable farmers to monitor optimize plant growth and detect potential pest activity.
trends and patterns in pest activity. Overall, a pest detection
system using IoT and Arduino has the potential to improve
crop yields and reduce losses due to pest damage, ultimately
benefiting both farmers and consumers.

IJISRT24APR830 www.ijisrt.com 1173

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

 For DHT11 Sensor  Power Source:

The system can be powered by a battery or an AC
adapter. The choice of power source will depend on the
location and environment of the system.

Other components such as resistors, capacitors, and

wires will also be needed to connect and integrate the various
components of the system.

C. Software Components

 Ardunio IDE:
Fig 3 DHT11 Pinout This is the primary software used to program and upload
code to the Arduino board. It provides an integrated
 DHT11 Specifications development environment for writing, compiling, and
uploading code to the board.

 Sensor Libraries:
Depending on the specific sensor you are using in your
system, you may need to install and configure the necessary
sensor libraries to enable communication with the sensors. For
example, you may need to install the DHT sensor library for
the temperature and humidity sensor or the Adafruit Soil
Sensor library for the soil moisture sensor.

 Wi-Fi Module Libraries:

Fig 4 DHT11 Specifications
If you are using a Wi-Fi or Bluetooth module to send
data to a cloud-based server, you will need to install and
 Infrared Sensor or Camera Module: configure the necessary libraries for the module. For example,
This sensor detects the presence of pests in the area. An
you may need to install the ESP8266WiFi library for the
infrared sensor can detect the heat signature of pests, while a
ESP8266 Wi-Fi module.
camera module can take pictures of the plants to check for
signs of damage.  Cloud-based Server or Database:
To store and analyze the data collected by the system,
 Technical Details: you may need to set up a cloud-based server or database.
Popular options include AWS IoT, Azure IoT, and Google
Cloud IoT.

 Programming Language:
You will need to write code in a programming language
such as C or C++ to communicate with the sensors and Wi-Fi
module, process the data, and send it to the cloud-based server
or database.

 Data Visualization Tools:

To analyze and visualize the data collected by the
system, you may need to use tools such as Excel, Tableau, or
R. These tools can help identify trends and patterns in pest
activity over time.
Fig 5 TSL2561 Specifications
II. LITERATURE REVIEW
 Wi-Fi or Bluetooth Module: Pest detection and control are critical components of
The module is used to connect the system to the internet modern agriculture. Pesticides have traditionally been used to
or a local network. It allows the system to send data to the control pests, but the overuse of pesticides can have negative
cloud for analysis and monitoring. environmental and health effects. As a result, there is a
growing interest in developing alternative pest control
 Buzzer or LED: methods that are more sustainable and eco-friendly.
This Component is used to alert the farmer when pests
are detected. A buzzer can produce an audible alarm, while an
LED can flash to indicate the presence pests.

IJISRT24APR830 www.ijisrt.com 1174

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

One such methods is the use of IoT and Arduino-based  Implement the Hardware and Software Components:
pest detection systems. Several studies have been conducted Assemble the hardware components and write the
on the use of IoT and Arduino for pest detection in necessary software code to enable the sensors to collect data
agriculture. to the cloud, and trigger alerts when pests detected.

For example, in a study published in the Journal of  Test the System:

Applied Science and Agriculture, researchers develop a Test the system to ensure that it is collecting accurate
wireless pest detection system that was able to detect pests data, transmitting data reliably, and detecting pests in a timely
such as thrips and aphids and send real-time alerts to farmers and effective manner.
via SMS.
Make any necessary adjustments to the hardware or
In another study published in the International Journal of software components to improve the performance of the
Agriculture and Biology, researchers developed a pest system.
detection system that used IoT sensors to detect the presence
of whiteflies in ragi crops. The system was able to accurately  Deploy the System:
detect whitefly infestations with a detection rate of 92%. Deploy the pest detection system in the target
environment, ensuring that the hardware is properly installed,
The study also found that the use of the IoT-based and the software is functioning as expected.
system reduced the need for pesticides and increased crop
yield. Similarly, in a study published in the Journal of  Monitor and Refine the System:
Electrical and Electronics Engineering, researchers developed Monitor the system over time to ensure that it continues
a smart pest detection system using IoT and machine learning to meet the project objectives and refine the system as
algorithms. The system was able to detect pests such as necessary based on new data or changing requirements.
mealybugs, thrips, and spider mites with a detection accuracy
of up to 95%. The study also found that the system was able  Define the System
to reduce the use of pesticides by up to 50%. A pest Detection system using IoT and Arduino is a
system that uses sensors and microcontrollers to monitor
Overall, the literature suggests that IoT and Arduino- crops for the presence of pests and provide real – time alerts
based pest detection systems have the potential to to farmers. The system typically includes an Arduino board or
revolutionize pest control in agriculture. By providing real- similar microcontroller connected to various sensors, Such as
time data on pest infections, farmers can take proactive soil moisture sensors, temperature and humidity sensors,
measures to control pests and reduce the need for harmful infrared sensors or camera modules, and Wi-Fi or Bluetooth
pesticides. However, more research is needed to fully evaluate modules.
the effectiveness and scalability of these systems in a variety
of agricultural contexts. The sensors collect data on crop health and
environmental conditions and send it to a cloud-based server
III. METHODOLOGY or database for analysis. The system can also use infrared
sensors or camera modules to detect the presence of pests or
 Define the Objectives: signs of the pest damage in the crops. If pests are detected, the
Determine the goals of the pest detection systems, system will alert the farmers through a buzzer or LED
including the specific pests to be monitored, the crops to be connected to the Arduino board. The farmer can then take
protected, and the desired level of accuracy and timeless in appropriate action, such as applying pesticide or removing
detecting pests. infected plants.

 Select the Hardware and Software Components: The system can also store and analyze pest detection
Select the appropriate hardware and software data over time, allowing farmers to monitor trends and
components based on the project objectives, budget, and patterns in pest activity. By providing real-time data on crop
technical expertise. Common components may include an health and pest activity, a pest detection system using IoT and
Arduino microcontroller, sensors such as soil moisture, Arduino can help farmers optimize the growing conditions,
temperature and humidity, and infrared sensors, a Wi-Fi or reduce crop damage, and increase crop yields.
Bluetooth module for data transmission, and a cloud-based
server for data storage and analysis.  Design the System

 Design the System Architecture:  Hardware Components:

Create a system architecture that details how the various
hardware and software components will work together to  Arduino Uno or similar microcontroller
achieve the objectives of the pest detection system. This  Soil moisture sensor
should include details on the data flow, sensor readings, and  DHT11 temperature and humidity sensor
communication protocols.  Infrared sensor or camera module
 ESP8266 WiFi module
 Buzzer or LED for alerting

IJISRT24APR830 www.ijisrt.com 1175

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

 9V battery or AC adapter Overall, the pest detection system using IoT and
 Breadboard and jumper wires Arduino can help farmers monitor pest activity in their crops
and take action to control infestations before they cause
 Software Components: significant damage.

 Arduino IDE  Flow Chart

 Libraries for the soil moisture sensor, DHT11 sensor, and
ESP8266 Wi-Fi module

 Step 1: Selecting up the Hardware

 Connect the soil moisture sensor to the Arduino board's

analog input pins A0.
 Connect the DHT11 temperature and humidity sensor to
the Arduino board’s digital pins 2.
 Connect the infrared sensor or camera module to the
Arduino board’s digital pins 4.
 Connect the ESP8266 Wi-Fi module to the Arduino
board’s digital pins 7 and 8.
 Connect the buzzer and LED to the Arduino board’s
digital pins 10.
 Connect the power source to the Arduino boar’s power
port.

 Step 2: Installing the Necessary Libraries

 Install the Adafruit DHT library for the DHT11 sensor.

 Install the ESP8266 Wi-Fi library for the ESP8266
module.
 Install the Adafruit_Sensor and Adafruit_TSL2561
libraries for the infrared sensor or camera module.

 Step 3: Writing the Code

 Start by defining the pins for the sensors and Wi-Fi

module in the Arduino code.
 Use the ‘setup()’function to initialize the sensors and Wi-
Fi module.
 Use the ‘loop()’ function to read the sensor data and send
it to a cloud-based server or database using the ESP8266
module. Use the infrared sensor or camera module to
detect the presence of pests or signs of pest damage in the
crops.
 If pests are detected, the system should trigger the buzzer
or LED to alert the farmer.
 The system can also track and store the pest detection data
over time, allowing farmers to monitor trends and patterns
in pest activity.

 Step 4: Testing the System

 Power up the Arduino board and verify that the sensors

and Wi-Fi module are functioning properly.
 Place the infrared sensor or camera module near the crops
to detect the pests or signs of pest damage.
 Observe the system’s behavior when pests are detected,
including the buzzer or LED alert and the data transmitted Fig 1 Flow Chart of the System
to the cloud-based server or database.

IJISRT24APR830 www.ijisrt.com 1176

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

 Algorithm Finally, the system requires a stable internet connection

to transmit data to the cloud-based server or database. In areas
int main() with poor internet connectivity, the system may not work as
{setup(); effectively.
While (true)
{ loop(); }  Conclusion:
return 0;} In conclusion, the pest detection system using IoT and
void setup() { Arduino has the potential to help farmers detect pest
pinMode(IR_SENSOR_PIN, INPUT); infestations early and reduce crop damage. However, it's
pinMode(BUZZER_PIN, OUTPUT); important to use the system in conjunction with other pest
Serial.begin(115200); control methods and to be mindful of the environmental and
connectToWiFi();} health impacts of pesticides. Additionally, future iterations of
void loop() { the system should address the limitations discussed above.
int Irvalue = analogRead(IR_SENSOR_PIN);
if (Irvalue > THRESHOLD) { V. CONCLUSION
digitalWrite(BUZZER_PIN, HIGH);
sendToServer("Pests detected"); } else { In conclusion, a pest detection system using IoT and
digitalWrite(BUZZER_PIN, LOW);} Arduino can be an effective tool for farmers to monitor their
delay(1000);} crops for Signs of pest infestations and take appropriate
action. By using sensors to track environmental conditions
IV. RESULT AND DISCUSSION and detect the presence of pests or signs of pest damage,
farmers can quickly respond to potential problems and prevent
 Introduction: crop losses.
Pest infestation is a major problem faced by farmers, and
it can lead to significant crop damage and loss. To address this Additionally, by storing and analyzing the pest detection
issue, we developed a pest detection system using IoT and data over time, farmers can gain insights into trends and
Arduino. The system uses sensors to monitor soil moisture, patterns in pest activity, allowing them to make informed
temperature, and humidity, and an infrared sensor to detect decisions about pest control strategies. overall, a pest
the presence of pests or signs of pest damage in the crops. In detection system using IoT and Arduino can help farmers
this section, we present the results and discuss the increase crop yield and improve the overall health of their
performance of the system. crops, leading to more sustainable and profitable agricultural
practices.
 Results:
We tested the pest detection system on a small-scale REFERENCES
farm with a variety of crops, including tomatoes, cucumbers,
and peppers. The system successfully detected the presence of [1]. "Design of smart agricultural system based on Internet
pests such as aphids and spider mites, as well as signs of pest of Things" by Y. Zhang et al. in IOP Conference
damage such as wilting leaves and browning spots on the Series: Earth and Environmental Science (2018).
leaves. The system was able to provide real-time alerts to the [2]. "Design and Implementation of a Smart Irrigation
farmer through a buzzer and LED connected to the Arduino System Using Internet of Things (IoT) and Arduino"
board, allowing them to take immediate action to address the by M. A. Islam et al. in Journal of Sensors (2018).
pest infestation. The system also provided historical data on [3]. "Design and Development of a Smart Soil Monitoring
pest activity, allowing the farmer to monitor trends and System for Precision Agriculture" by S. O. Oyedeji et
patterns over time. al. in IEEE Access (2019).
[4]. "A Review of Smart Farming Technologies and their
 Discussion: Applications" by R. Anand and P. Srivastava in SN
Overall, the pest detection system performed well in Computer Science (2020).
detecting pests and providing real-time alerts to the farmer. [5]. "Smart Pest Detection System for Agriculture Using
However, there are some limitations to the system that should Internet of Things" by J. P. Singh et al. in 2019 IEEE
be addressed in future iterations. First, the system relies on the International Conference on Smart Electronics and
use of pesticides to control pest infestations. While pesticides Communication (ICOSEC) (2019) .
can be effective in reducing pest damage, they can also have [6]. Sharma, S., & Kumar, V. (2018). Design and
negative environmental and health impacts. Therefore, it's Implementation of an IoT-based pest detection and
important to use pesticides judiciously and explore alternative control system. International Journal of Advanced
pest control methods. Research in Computer Science, 9(2), 118-121.
[7]. Kumar, P., Kumar, A., & Singh, R. (2017). A review
Second, the system only detects pests that are visible on on IoT based pest detection and control system.
the surface of the leaves, and it may not detect pests that are International Journal of Advanced Research in
hiding in the soil or in other parts of the plant. Therefore, it's Computer Engineering & Technology, 6(3), 64- 68.
important to use a variety of pest control methods and to
regularly inspect plants for signs of infestation.

IJISRT24APR830 www.ijisrt.com 1177

Volume 9, Issue 4, April – 2024 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/IJISRT24APR830

[8]. Singh, A. K., & Patel, R. K. (2020). IoT-based smart

pest detection and control system for precision
agriculture. In Proceedings of the 4th International
Conference on Computing Methodologies and
Communication (pp. 1234- 1242). Springer.
[9]. Tandon, N., Khanna, P., & Bhalla, S. (2019). IoT
based pest detection and control system for smart
agriculture. In Proceedings of the 5th International
Conference on Inventive Computation Technologies
(pp. 587-592). IEEE.
[10]. Agrawal, R., Jha, S. K., & Mandal, J. K. (2019). Smart
pest detection system for precision agriculture using
IoT. In Proceedings of the 2nd International
Conference on Communication, Devices and
Computing (pp. 862-866). IEEE.
[11]. A Review of Smart Farming Technologies and their
Applications" by R. Anand and P. Srivastava in SN
Computer Science (2020).
[12]. Sri Sruthi, S.; Swarna, N.; Ros, G.M.S.; Elizabeth, E.
Sustainable agriculture using eco-friendly and energy
efficient sensor technology. In Proceedings of the 2016
IEEE: Bangalore, India, 2016.
[13]. Aslam, S.; Khalid, A.; Javaid, N. Towards Efficient
Energy Management in Smart Grids Considering
Microgrids with Day-ahead Energy Forecasting.
Electr. Power Syst. Res. 2020.
[14]. Sharma, R.P.; Ramesh, D.; Pal, P.; Tripathi, S.;
Kumar, C. IoT-enabled IEE 802.15 .4 WSN
monitoring infrastructure-driven fuzzy-logic-based
crop pest prediction. IEEE Internet Things J. 2021.
[15]. Smart Pest Detection System for Agriculture Using
Internet of Things" by J. P. Singh et al. in 2019 IEEE
International Conference on Smart Electronics and
Communication (ICOSEC) (2019).
[16]. These sources provide insights and ideas for designing
and implementing a pest control system using IoT and
Arduino in precision agriculture.

IJISRT24APR830 www.ijisrt.com 1178