Team 28

Team Members :

NamePhoneResumeLinkedInGithubWuzzufEmail
Mohamed Alzahaby (Leader)+20 101 114 4724Click
Me		Click
Me		Click
Me		Click
Me		mohamed1501643@miuegypt.edu.eg
mohamedazahaby@gmail.com
Moataz Samir+20 114 446 6365Click
Me		Click
Me		Click
Me		Click
Me		moataz1604232@miuegypt.edu.eg
moatazsamir36@gmail.com
Khalid Walid+20 111 016 7471Click
Me		Click
Me		Click
Me		Click
Me		hazem1608450@miuegypt.edu.eg
Hazem Alaa Eldin+20 106 732 4655Click
Me		Click
Me		Click
Me		Click
Me		khaled1602323@miuegypt.edu.eg

Supervisors :

Project Description :

A mobile application that can detect palm trees common diseases such as leaf spots and blight spots by using normal mobile cameras and can detect a lethal pest called Red Palm Weevil by acquiring thermal images of palm trees using thermal USB camera which can be connected to smartphones.

Documents :

Proposal :

Proposal_DOCDownload
Proposal_PPTDownload

Software Requirements Specifications (SRS) :

SRS_DOCDownload
SRS_PPTDownload

Software Design Documentation (SDD) :

SDD_DOCDownload
SDD_PPTDownload

Thesis Document:

Thesis_DOCDownload
Thesis_PPTDownload

DELL EMC Documents:

First Phase ReportDownload
Second Phase ReportDownload
Second_phase PowerPointDownload
Final Phase ReportDownload

Achievements:

Ranked 5th among Africa, Middle East and Turkey in Dell EMC Competition

link: CLICK ME

Publications:

  1. An Intelligent Approach for Detecting Palm Trees Diseases using Image Processing and Machine Learning
    • publisher: International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.
    • Link: Click ME
    • Abstract: 
      • Today’s palm trees diseases which cause a huge loss in production are extremely hard to detect either because these diseases are hidden inside the texture of the palm itself and cannot be seen by naked eyes or because it appears on its leaves which are hardly examined due to how far they really are from the ground. In this paper we’re interested in detecting three of the most common diseases threatening palms today, Leaf Spots, Blight Spots and Red Palm Weevil. Diagnosis of these diseases are done by capturing normal and thermal images of palm trees then, image processing techniques were applied to the acquired images. Two classifiers were used, CNN to differentiate between Leaf Spots and Blight Spots diseases and SVM for Red Palm Weevil pest. The results for CNN and SVM algorithms showed a success rate of accuracy ratio 97.9% and 92.8% respectively, these results are considered to be the best results in this domain as far as we know. The paper also includes the first gathered thermal images dataset for palms infected with Red Palm Weevil and healthy palms as well.
  2. A Survey on Detection of Red Palm Weevil Inside Palm Trees:Challenges and Applications
    • publisher: International Journal of Machine Learning and Computing (IJMLC), indexed by Scopus
    • Status: Accepted 
    • Publish Date: Postponed to November 11-13, 2020 due to Covid-19
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Dell EMC video:

Demo:

User Experience:

palm_care_user_experience