The urge to fully automate farming process to prevent human intervention for more efficient and modernized system. The idea for our project is to create a Computer Vision based 6-DOF Manipulator that would be used in farming to take care of plants of different types and differentiate betwe
AI BASED PLANT DETECTION AND CARE ROBOT
The urge to fully automate farming process to prevent human intervention for more efficient and modernized system. The idea for our project is to create a Computer Vision based 6-DOF Manipulator that would be used in farming to take care of plants of different types and differentiate between plants and weeds. Convolutional Neural Network would be used to detect different kinds of weeds. Once, weed detected, then the 6-DOF Manipulator will comes into action and remove the weeds physically. Moreover, it will be used for disease detection and taking care of a specific plant.
Environmental friendly weeding:
One of our goal to build this project is to build an environmental friendly Robot that would be used to remove weeds without affecting the environment. Most of pesticide and herbicide have very bad impact on environment. They are one of the main reasons of soil and water pollution. Our aim is to build a Computer Vision based machine that can remove weeds without affecting environment.
Disease detection:
There are no better options than machines to take care of plants efficiently. There are large number of diseases in plants. Due to human errors in disease detection, computer vision-based machines will be best option. So, our project will detect disease and inform owner to take actions to control disease as soon as possible for lesser damage
Efficient productivity:
In efficiency machines have to match. They can work days and nights without taking rest. So, our robot will increase efficiency in productivity.
Watering:
It can give water to plants according to the requirements.
Reduction of human labour:
As population of humans increase the more food will be required. Farming robots will reduce human labour.
Cost effective:
Over a long period of time, it can reduce cost of productivity.
The main classifier of the system is a Convolutional Neural Network (CNN), which is a network, made up of different types of layers of neurons or perceptron.
In this project, we will use Convolutional Neural Network (CNN) and Computer Vision to differentiate between weeds and crops with the help of a camera. CNN will tell us weather the plant is a weed or our desired crop. A 6 DOF Manipulator Robotic Arm will be used to remove that weed.
First data sets of different weeds and diseases will be collected by image processing and a robot (6-DOF manipulator) will be trained by using machine learning algorithms (Artificial Intelligence).
In conventional modern farming, different kinds of chemical pesticides, herbicides are used to control insect pests and weeds. Herbicides are poisons that kill the causal organisms, but some of them can also harm wildlife and humans, as well as pollute the natural resources (soil and water) and the broader environment.
The most dangerous operation in farming is the handling and application of chemical Herbicides. An estimated 200,000 deaths a year occur worldwide due to acute pesticide and herbicides poisoning due to poor handling and use.
Our aim is to build an environmental friendly Computer Vision based 6-DOF Manipulator that can remove weeds physically without affecting wildlife and environment. Moreover, by using machines the efficiency of productivity will definitely increase. And it will fully automate the farming process.
Following is the list of deliverables:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 6-DOF Manipulator | Equipment | 1 | 50000 | 50000 |
| Total in (Rs) | 50000 |
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