Leafix

This system can be proved beneficial for the farmers for early detection of Plant Diseases. Through machine learning and inclusion of diverse images will make the detection and solution more precise and effective. The system is developed into a sophisticated interface in the form of an Android Appli

Project Title

Leafix

Project Area of Specialization

Artificial Intelligence

Project Summary

This system can be proved beneficial for the farmers for early detection of Plant Diseases. Through machine learning and inclusion of diverse images will make the detection and solution more precise and effective. The system is developed into a sophisticated interface in the form of an Android Application in order to be a great asset to the agricultural sector. In the future this methodology can be integrated with other yet to be developed methods for disease identification and classification. The use of other techniques can be explored to enhance the efficiency of the system in future.

Project Objectives

Following are the objectives/outcomes the system will provide:

? Maximize crop growth and agricultural efficiency.

? Precise analyze leaf’s features and make reasonable approaches in curing the disease in real-time.

? Less resource consumption and low loss of crop.

? Prevention of diminishing arable lands and depletion of natural agricultural resources.

? Increase in potential productivity and quality of agricultural output.

? Emphasis on sustainable plant disorder management strategies that ensure crop security.

? Better quality of crop resulting in better export and higher return value.

Project Implementation Method

1) First of all we will take our dataset of plants/ leaves and disease.

2) We will use google teachable to train our model and it will be ready.

3) The user will signup and login into the application.

4) User will capture the image of the leaf/plant using his app camera.

5) it will be passed to the classifier the algorithm we have used will then check and categorize it accordingly in which category the image will fall. Resulting in giving what diseases it has and giving mitigation

Benefits of the Project

This project is beneficial for the farmers and as long it will make an impact on the economic chapter of the country caused in the agriculture sector we get a big loss every year just cause the disease makes the crops and other plants dull. although through this application we will take good care of our farms and make it happen.

Technical Details of Final Deliverable

1. Local Dataset (Module 1) A resourceful categorization of images and their respective diseases in the local storage for future consultation. A self-collected dataset will include a. Specifying Dataset b. Manual download and extraction c. Specifying dataset splits d. Dataset configuration e. Dataset Testing

2. Image Labeling (Module 2) All the images stored in the dataset will be labeled and classified to provide coordinates of the leaf by hard coded XML files.

3. Data augmentation (Module 3) Custom augmentation of data to enhance performance of our Deep Learning model. a. Convert .xml files into one .csv file b. Apply data augmentation pipeline c. Convert resulting .csv file into multiple .xml files

4. Model Retraining (Module 4) A machine learning model is a function with learnable parameters that maps an input to a desired output. The optimal parameters are obtained by training the model on data. a. Getting a batch of data to the model. b. Asking the model to make a prediction. c. Comparing that prediction with the "true" value. d. Deciding how much to change each parameter so the model can make a better prediction in the future for that batch. 5

5. Login/ Signup (Module 5) User to signup and login to the application to keep record of the account and make the user experience more personal and fit for their particular use

6. Profile Management (Module 6) Manage profile with login and other settings. 7. Evaluation (Module 7) A resourceful categorization of images and their respective diseases in the local storage for future consultation. 8. Multilingual Recommendations (Module 8) Application to support multi-languages to incorporate better understanding for the local user and another foreign user. This will recover the understanding lag which might be caused due to language barrier.

Final Deliverable of the Project

Software System

Core Industry

Agriculture

Other Industries

Health

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Decent Work and Economic Growth

Required Resources

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