Chicken Disease Prediction System
Many chicken farmers find it difficult to identify the disease and treat the disease on time. They need to consult an animal doctor which is costly and time consuming. And sometimes the chicken dies for not getting on time treatment and the chicken farmer gets a loose. The purpose of our proj
Project Title
Chicken Disease Prediction System
Project Area of Specialization
Project Summary
Many chicken farmers find it difficult to identify the disease and treat the disease on time. They need to consult an animal doctor which is costly and time consuming. And sometimes the chicken dies for not getting on time treatment and the chicken farmer gets a loose.
The purpose of our project is to solve the problem of chicken farmers as they can identify if the chicken has disease and treat it on their own. Here we are trying to make a prediction of the chicken disease with just a chicken poop image.
Our model predicts the chicken disease by just taking the images of the chicken poop through the mobile application and feeding them into the learning model and our model will predict the disease. Using this app/system we can predict the chicken disease for the purpose of treatment.
Project Objectives
The main purpose of the system is to help the chicken farmer treat the diseased chicken and keep them healthy. The system will predict the disease and its suitable treatment.
- Poop augmentation and detection
- Early detection of chicken diseases
- Reduce cost of treatment.
- Provide most suitable, less costly treatment.
- Maintain health of chicken
Project Implementation Method
We will use different techniques in order to achieve accurate estimation of chicken disease images. Firstly we will apply image filters ,then extract image features. After it, Convolution Neural Networks(CNN) for image classification will be used. If ,CNN does not generates results accordingly then a pre-trained model will YOLL will be used. There are different versions of YOLO, and in this study we modified and used YOLO900 (also known as YOLOv2), and as such, we refer to YOLO900 as YOLO. Compared to other state-of-the art methods that treat detection, classification and region extraction as different problems. Our mobile application is based on given frameworks.
- Flutter
- Firebase
- FirebaseDatabase
- REST Full API
Benefits of the Project
- Predict the disease of chickens by scanning the image of their poop.
- Suggest suitable treatment for the disease.
- Predict an affordable and healthy diet for chicken.
- Refer an affordable doctor if the disease is serious or needs special medication reatment.
Technical Details of Final Deliverable
We will develop a mobile app and web app which will predict chicken disease by scanning chichken droppings.
The number of disease which we will predict will be more then previous approaches.
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Camera | Equipment | 1 | 20000 | 20000 |
| Gpo laptop | Equipment | 1 | 50000 | 50000 |
| Total in (Rs) | 70000 |
If you need this project, please contact me on contact@adikhanofficial.com
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