AGRI CROPTRACKER SENSEFLY

Our project intends to build a classifier which will classifies the plants on the basis of their disease. Our idea is to introduce an automated solution for this lead by drone gathering the data of the field from aerial perspective, as drone take survey over the agriculture fields containing hardwar

Project Title

AGRI CROPTRACKER SENSEFLY

Project Area of Specialization

Artificial Intelligence

Project Summary

Our project intends to build a classifier which will classifies the plants on the basis of their disease. Our idea is to introduce an automated solution for this lead by drone gathering the data of the field from aerial perspective, as drone take survey over the agriculture fields containing hardware with it that will be cameras for image source used in image processing, various sensors such as (humidity, temperature and pollution sensors) and pesticide or med sprayer ending up displaying the result of what conditions are there in the field through a web monitoring system.

Project Objectives

Here why we proposing our idea of introducing automation in the care of crops through DRONE and our Web Based Monitoring System as well as a Medic solution for agricultural fields.

Project Implementation Method

Implementation of our project follows as the Drone will be responsible to survey and monitor the fields by capturing the environment conditions over the farm using humidity sensor, gas sensor for monitoring pollution and images with camera attached on it, on back-end which is going to be image processed by data set in the ANN to alert if there is any problem with the crop or not by displaying it on our Web Monitoring System.

Benefits of the Project

Following are the features that make our project unique in comparison with the existing ones and it will make easy for the evaluators to understand our project

• Drone surveillance:

Providing aerial drone survey for monitoring the condition over the agriculture fields instead of manual checkup of the giant fields making as ease for the farmers 

• Detecting plant is healthy or unhealthy:

It will detect whether the plant is healthy or unhealthy using a camera fixed in a drone, image processing and machine learning.

• Crop scouting:

A quality drone and multispectral camera system can detect disease and stress early (sometimes before it is visible from the ground or with standard color cameras). Use this information, coupled with proven agronomic methods, to focus your treatment plans

• Recommending pesticide for infected plant:

After detecting the plant is healthy or unhealthy, if it is unhealthy it recommend us the suitable pesticide to spray on the infected plant using ANN (Artificial Neural Network).

• Time Saving:

It will be time consuming for farmers to check health of plants manually. With this technology it will be time saving.

• Environment monitoring :

 It will have environment sensors such as humidity, temperature and gas sensors .That will help us to understand the environment.

• Pesticide or Medicine sprayer:

Drone sprayers are able to navigate very hard to reach areas, such as steep tea fields at high elevations. Drone sprayers save workers from having to navigate fields with backpack sprayers, which can be hazardous to their health. Drones sprayer delivery very fine spray applications that can be targeted to specific areas to maximize efficiency and save on chemical costs

Technical Details of Final Deliverable

1. DRONE: (DJI SPARK)
2. Image processing
3. Computer vision
4. Artificial neural network (ANN)
5. Python programming language
6. Web-Based Monitoring
7. 360 view camera
8. Google colab
9. Gas sensor
10. Humidity sensor

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Agriculture

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Life on Land

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com