IOT Based Pest Prediction by Using Machine Learning

Project Title

IOT Based Pest Prediction by Using Machine Learning

Project Area of Specialization Computer ScienceProject Summary

Pakistan is highly dependent on agriculture. The economy of Pakistan can only be good if we make innovations in the field of agriculture with the help of modern technology. Our farmers use manual methods that keep pace with growth.

In order to increase the yield of the crop, steps have to be taken against the pest that is attacking it, just as the locusts have recently wreaked havoc. We want to create a digitally revolutionary systemin which even before the arrival of pests, can be detected the surrounding environmental elements and can report any pest before its attack.

The farmer will be able to know from their mobile app and take Prevention measures against Pest attacks.

With the help of Machine Learning and IoT system, Our farmer will be able to avoid huge losses with the help of IoT based Pest Prediction and will be able to get more yields to increase the economy of the country and the nation. 

Project Objectives

We want to improve the yields of crops with the help of Machine Learning and IoT systems. The farmer will be able to get POP messages of Pest prediction on their android mobile app.

We want to change the style of the agriculture manual to digital.

We want to create a digital system in which pests can be predicted before the attack.

By use of this information, our farmer will take preventative measures against the Pest attack before its arrival, and agriculture expenses will be low and the farmer will increase the yields.

Project Implementation Method

Use Waterfall Method:

We will breakdown down project activities into linear sequential phases, where each phase depends on the deliverables of the previous one and corresponds to a specialization of tasks.

Requirement Gathering
Analysis Read
System Design
Implementation of modules
Testing of modules
Deployment
Maintenance
.

In the pest prediction system, we get environmental factor information that causes the pest arrival.

First of all, we will get the value from sensors such as temperature, Humidity, Wind Speed, Rainfall, CO2, and Light Intensity. We will use Adreno with multiplexer which will be connected with the wifi module.

All the information will be sent to the IoT Server then we will apply machine Learning Algorithms which will be written in python. Then we will embed the python code in the android app. So that all the calculated information will be represented in a better way to the farmers for their easy understanding.

Benefits of the Project

Some Benefits of the Pest Prediction System is given below:

• Increase yelid of crops
• Information of Pest Prediction through mobile App
• Easy to use
• Availability 24 hours
• Alarming

Technical Details of Final Deliverable

Sensors:

• Temprature
• Humidity
• Wind Speed
• Rainfall
• CO2
• Light Intensity

Devices:

• Ardunio
• IoT Server

Languages and Algorithms:

• Python
• Java
• C++
• Machine Learning (Artificial Neural Network)

IDE:

• PyCharm
• The Arduino Integrated Development Environment
• Android Studio

OS:

• Ubantu
• Windows

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Agriculture Core Technology Internet of Things (IoT)Other Technologies Big DataSustainable Development Goals Zero Hunger, Decent Work and Economic Growth, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
Temperature/ humidity Sensor	Equipment	5	800	4000
Rainfall Sensor	Equipment	5	500	2500
Co2 Sensor	Equipment	6000	3	18000
Light Intensity Sensor	Equipment	1000	5	5000
Wind Speed Sensor	Equipment	15000	1	15000
Arduino board	Equipment	500	5	2500
WF Wifi Module	Equipment	600	5	3000
Multiplexer	Equipment	2000	5	10000
UPS	Equipment	10000	1	10000
POl, Travelling, Paper etc	Miscellaneous	10000	1	10000