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
IOT Based Pest Prediction by Using Machine Learning
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.
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.
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.
Some Benefits of the Pest Prediction System is given below:
Sensors:
Devices:
Languages and Algorithms:
IDE:
OS:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 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 |
| Total in (Rs) | 80000 |
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