Dr Plant

style="direction: ltr;">It is efficient for farmers. It develap app for easily understand for human. It is leaf disease diagnose .detection. Agricultural production is essential to the economic development of any country. That?s why disease identification in plants and vegetable is cr

Project Title

Dr Plant

Project Area of Specialization

Artificial Intelligence

Project Summary

It is efficient for farmers. It develap app for easily understand for human. It is leaf disease diagnose .detection. Agricultural production is essential to the economic development of any country. That’s why disease identification in plants and vegetable is critical in the agricultural sector, as a disease in plants is a regular occurrence. If reasonable precautions are not taken on time, plants can significantly affect the environment, affecting product quality, quantity, and productivity.Lemons and oranges are our fruits.A study of automatic illness recognition and classification methods are also discussed. We explore different methods for pre-processing, segmentation, extraction of features and grouping. Discuss also the relevance of functional extraction and techniques of deep learning. we intend to develop a system that will assist in detection of diseases in citrus leaves. Farmers face great loss in production of citrus crops due to unawareness of disease. Our proposed system will be able to detect diseases on citrus leaf in early stages. The solution we are going to implement will be easily accessible[4] . The proposed solution will use a camerathat will take images of the leaf and then our program will detect the disease. Our system will be able to detect disease revolving around Orange (citrus) fruit. The scope of disease detection in this system is limited to certain number of diseases being found in Citrus fruits.

 

Project Objectives

•In this system we are going to develop android mobile application.

•Use android camera that will take the images.

•Check and find the disease by using the help of android phone

•Check the diagnoses and give some solution . 

•We add a doctor that will be direct communicate with your clients.

Project Implementation Method

This research aims to compare two types of image namely Grayscale and RGB. Both images are subjected to pre- processing, segmentation and clustering for detecting leaves diseases. This research concludes that the color becomes an important feature when subjected to diseases detection[3].  Both types of images are subjected to median filter for image enhancement and segmentation for extraction of the disease portion which are used to identify the disease level.                                                 Plant Leaves Disease detection by using Image Processing(Deep Learning)                                                                                   In this research, we review the need of plant leaves disease detection system that would facilitate advancement in agricultural. By getting early information regarding crop health and disease detection it can facilitate the control of diseases throughout the crops. The major techniques of plant disease detection are BPNN, SVM, K-means clustering, and SGDM. These are the technique used to analyze the healthy and diseased plants leaves.

Outcomes and challenges of citrus greening disease

This research describes an imaging system with potential for airborne detection of plant greening disease. Controlled evaluation was carried out on leaf samples from a greenhouse, followed by validation on diseased and healthy plant trees at an orange grove in Lake Alfred, Florida. By using UAV platform, using UAV-mounted sensor suite for detection of plant greening disease in early stages and avoid catastrophic loss of crop fields. 
Identification of Citrus Huanglongbing Disease at the Pre-Symptomatic Stag :
Identification of plant Huanglongbing Disease at the Pre-Symptomatic Stage is achieved by using Polarized Imaging Technique. Huanglongbing (HLB), also known as yellow shoot or plant greening, is a devastating disease, associated with ‘CandidatusLiberibacterasiaticus (CLas).’ Unfortunately, there is no effective cure for this disease, and since a tree is infected, it will eventually die

KKN classifier 

? CNN.                              
? K-means 
? Hybrid Algorithm 
We will use:  
? Machine Learning 
? Python 
? Android Studio 
? Image Processing.

Benefits of the Project

Farmer easily understand the app and easily see the leaf to detect before damage the leaf.

Our agriculture is a very good in this industry so w can provide the solution of this problem.

Our global cost is almost is a agriculture industry so we can easily relate this situation and good solution discovered to our economy budget.

Our Aim is that farmers is so hardworking and sudendly damage the crops so that i can developed this type of app to easily use our farmers to detect disease and then find the solution.

 

Technical Details of Final Deliverable

Language used for this software will only be English.

2) The android SDK version should be greater or equal to 16

3) We will use java as language for development.

App doesn 't work correctly 

System is damage.

Model is not train correctly 

100% accurary is not possible in that time.

Final Deliverable of the Project

Software System

Core Industry

Agriculture

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Required Resources

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