MAHARASHTRA STATE BOARD OF TECHNICAL EDUCATION,MUMBAI
GOVERNMENT POLYTECHNIC,BEED
[Institute Code:0032 ]
MICROPROJECT
Course & Code: Mobile Application Development [22617]
Title of Micro project: Disease Detection App
Mr. Jadhav Sir
Dr. A.K.waghmare
Dr.M.R.lohkare
Subject Teacher
Head of Department
Principal
Seal of
institute
1
MAHARASHTRA STATE BOARD OF TECHNICAL EDUCATION,MUMBAI
CERTIFICATE OF MICROPROJECT
This is to certify that following students of CM6I (Division-A/B) of
Diploma in COMPUTER ENGINEERING of the institute GOVERNMENT
POLYTECHNIC,BEED, Institute code:0032, have satisfactorily completed
MICROPROJECT work in subject/Course:
for
academic year 2023-24 as prescribed in the curriculum.
Roll
No.
Exam Seat
No.
335
Name of Student
Jadhav Aniket Vikas
Place:Beed
Mr. Jadhav Sir
Subject Teacher
Title of Microproject
“Disease Detection App”
Date:-- /-- -/2024
Dr. A.K.waghmare
Dr.M.R.lohkare
Head of Department
Principal
Seal of
institute
2
Teacher Evaluation Sheet
Name of Student:Aniket Vikas Jadhav
Enrollment No.2100320096
Programme: Computer Technology
Semester: 6
Course Title & Code: Mobile Application Development [22617]
Roll no: 335
Title of the Micro-Project: [In short]
 Disease Detection App
Course Outcomes Achieved:
• Interprete features of Android Operating System.
• Develop rich User Interfaces by using layouts and controls.
• Use User Interface components for android application development.
Evaluation as per Suggested Rubric for Assessment of Micro Project
Sr.
No.
Characteristic to be assessed
Poor
( Marks 1 - 3 )
Average
( Marks 4 - 5 )
Good
( Marks 6 - 8 )
Excellent
( Marks 9- 10 )
[A] Process and Product Assessment (Convert total marks out of 06)
1
2
3
4
Relevance to the course
Literature Review/information
collection
Completion of the Target as per
project proposal
Analysis and data representation
5
Quality of Prototype/Model
6
Report Preparation
Total Marks Out of (6)
[B] Individual Presentation/Viva (Convert total marks out of 04)
1
Presentation
2
Viva
Total Marks Out of (4)
MIcro-Project Evaluation Sheet
Process and Product Assessment
(6 marks)
(Note: The total marks taken from the above Rubrics is
to be converted in proportion of ‘6’ marks)
Individual Presentation/Viva
(4 marks)
Name and designation of the Teacher:
Dated Signature…………………………………………………………………………
Total Marks
10
(Lecturer in CM)
3
Annexure –I
Part – A Micro-Project Proposal
(Format for Micro-Project Proposal A about 2-3 pages)
Title of Micro-Project:
Disease Detection App
 Brief Introduction : The
Disease Detection of Crops app for Android is a mobile
application that harnesses the power of machine learning and computer vision
techniques to diagnose and identify plant diseases. With the capability to
analyze images of leaves, stems, and fruits, the app offers farmers, researchers,
and agricultural professionals an efficient and accurate means of detecting the
presence of crop diseases. As a low-cost and accessible tool, this app
represents an exciting development in agriculture and has the potential to
revolutionize the way we approach disease detection and management in
plants.
1.0
Aims/Benefits of the Micro-Project
• Provide an easy-to-use and accessible tool for farmers to detect and manage plant
diseases.
• Enhance the productivity and profitability of the agricultural sector by increasing crop
yields.
• To help farmers by taking timely actions to prevent further spread of diseases and
minimize crop loss.
• To contribute to the growth and development of the overall economy by enhancing the
performance of agriculture industries
2.0
Course Outcomes Addressed
• Interprete features of Android Operating System.
• Develop rich User Interfaces by using layouts and controls.
• Use User Interface components for android application development
4
3.0
Proposed Methodology
Step 1: Comprehensive study of the micro-project will be undertaken. I will thoroughly
analyze the project requirements and clarify any doubts independently.
Step 2: Information gathering will be conducted solely by me through extensive
research online and in relevant literature. I will collect various formats required for the
project, such as certificates and evaluation sheets.
Step 3: Formats will be finalized autonomously after reviewing the collected samples.
Step 4: The topic selection process will be solely my responsibility, considering the
availability of materials and my personal interests.
Step 5: I will independently list all the stationary items needed for the project and
create a budget accordingly.
Step 6: Budget discussions will be conducted individually, and the final amount will be
determined based on my analysis and considerations.
Step 7: Collection of data, photos, and information will be solely my task. I will gather
information from various sources and submit it to the project guide for review
Step 8: Printing or drawing will be carried out independently by me, and the final
output will be shown to the project guide for approval.
Step 9: I will prepare thoroughly for the oral/viva presentation, independently
explaining the project during the evaluation process.
5
5.0
Action Plan (Sequence and time required for major activity)
Sr.
No.
Planned
Start date
Details of activity
1
2
Collecting different formats
Finalization of formats in collaboration
3
Finalizing topic title
Listing stationary items required for project
along with budget
4
5
6
7
Planned
Finish
date
Name
budget and finalize the amount
Information collection
Report writing/Printing
6.0 Resources Required (major resources such as raw material, some machining facility,
software etc.)
S.
No.
Name of Resource/material
Specifications
Qty
Remarks
1
Computer,Mobile,Internet,Printer,Scanner
PC
01
Text book,Youtube,google
Techmax,www.youtube.com,www.google.co.in
-
Android Studio
IDE
Teachable Machine
Web Tool
2
3
4
1
1
6
Annexure – II
Part – B Micro-Project Report
(Outcomes after Execution) Format for Micro-Project Report (Minimum 6 pages)
Title of Micro-Project:
Disease Detection App
Table of Contents
Sr. No.
Topics
Page No.
1.
Rationale
8
2.
Aim/Benefits of the Micro-Project
8
3.
Course Outcomes Achieved
8
4.
Literature Review
8
5.
Actual Procedure Followed
9
6.
Actual Resources Used
9
7.
Outputs of the Micro-Project
10 - 18
8.
Skills Developed/Learning Outcomes of the Micro-Project
19
9.
Applications of this Micro-Project
19
7
1.0 Rationale
The rationale behind creating a disease detection app in Android is to provide farmers
and agricultural professionals with a quick and easy-to-use tool to detect and manage plant
diseases. This app utilizes advanced technologies such as image recognition, machine
learning, and artificial intelligence to accurately identify plant diseases, which can be
challenging for human eyes to detect. Farmers can save time and resources by detecting plant
diseases early on, allowing them to take timely actions to prevent further spread and
minimize crop loss, improve crop yields, and promote sustainable agricultural practices.
2.0 Aims/Benefits of the Micro-Project
• Provide an easy-to-use and accessible tool for farmers to detect and manage plant diseases.
• Enhance the productivity and profitability of the agricultural sector by increasing crop
yields.
• To help farmers by taking timely actions to prevent further spread of diseases and minimize
crop loss.
• To contribute to the growth and development of the overall economy by enhancing the
performance of agriculture industries.
3.0 Course Outcomes Achieved
• Interprete features of Android Operating System.
• Develop rich User Interfaces by using layouts and controls.
• Use User Interface components for android application development
4.0 Literature Review
Various reviews and article presented various image processing and machine learning-based
techniques for plant disease detection. The authors highlighted the potential of these
techniques in providing quick and accurate detection of plant diseases, leading to improved
8
crop yields and reduced economic losses. This study explored the use of smartphone-based
technologies for crop disease diagnosis in smallholder farms. Overall, the study suggests,
that the use of advanced technologies such as deep learning, machine learning, and artificial
intelligence has the potential to improve disease detection and management in crops.
Smartphone-based technologies also offer cost-effective and accessible solutions for farmers,
particularly smallholder farmers. The use of these technologies has the potential to increase
crop yields, promote sustainable agricultural practices, and contribute to the growth and
development of the agricultural industry
5.0 Actual Methodology Followed.
The aim of the Android-based disease detection app is to provide an easy-to-use and
accessible tool for farmers and agricultural professionals to identify and manage plant
diseases. To create this app, we conducted extensive research on various methods of
implementation. We opted to use the Teachable Machine web tool for our project, where we
created disease classes and trained the model using sample images. Upon exporting the
model as a tfile format, we integrated it into the Android Studio and designed a user interface.
The app's Java code prompts the user for camera permission to capture images, which the
model then analyzes and produces an output for. Through this process, we developed an
efficient and effective tool for disease detection in plants.
6.0
Actual Resources Used (Mention the actual resources used).
Sr. No.
Name of Resources
Required
Specifications
Qty
1.
Computer System
8 GB Ram and i5 processor
1
2.
MS Word
Latest
1
3.
Browser
Chrome
1
IDE
1
4
Android Studio
Remarks
9
7.0
Outputs of the Micro-Projects
(Drawings of the prototype, drawings of survey, presentation of collected data, findings etc.)
-----------------------------------------------------------------------------------------------------------
Disease Detection App

Source Code :activity_main.xml
10
11
12

MainActivity.java
13
14
15

Output :-
….…………….
16
….………………
17
18
8.0
Skill Developed / Learning outcome of this Micro-Project
▪
Developed a technical skill such as image processing, machine learning, and
app development.
▪
Developed a skill that involves creating an interface that is easy to use and
provides a positive user experience.
▪
Able to work with large datasets of plant images.
9.0
Applications of this Micro-Project
▪ A disease detection of crops app can help farmers detect diseases early and
prevent their
spread, leading to increased efficiency, productivity, and crop quality.
▪ The app can also help reduce the number of pesticides and other chemicals used
in agriculture,
leading to environmental protection and sustainability
19