01 Project Synopsis
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M.E. Project Report
M.E. Online Voting System with Face Recognition using Python Flask Report
Get structured M.E. Online Voting System with Face Recognition using Python Flask Report Final Year Project Report and Documentation with project objectives, methodology, system design, diagrams, implementation details, testing and complete project explanations. Suitable as a learning, documentation and project-presentation resource for students working on related final year projects.
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02 Detailed Project Report
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03 Customized Project Report
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Abstract
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Table of Content
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01
Introduction
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02
Problem Statement
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03
Existing System
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04
Proposed System
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05
Objectives
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06
System Architecture
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07
Major Functional Modules
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08
Hardware Requirements
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09
Software Requirements
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10
Future Enhancement
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11
Conclusion
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12
References
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Abstract
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Table of Content
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01
Chapter 1 — Introduction
- 1.1 Background of the Project
- 1.2 Problem Statement
- 1.3 Objectives of the System
- 1.4 Scope of the Project
- 1.5 Existing System Overview
- 1.6 Proposed System Overview
- 1.7 Technologies Used
- 1.8 Overview
- 1.9 Limitations
- 1.10 Advantages
- 1.11 Disadvantages
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02
Chapter 2 — Literature Review / System Study
- 2.1 Introduction
- 2.2 Review of Similar Systems
- 2.3 Comparative Analysis
- 2.4 Software Development Models
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03
Chapter 3 — System Analysis
- 3.1 Introduction
- 3.2 Functional Requirements
- 3.3 Non-Functional Requirements
- 3.4 User Requirements
- 3.5 Feasibility Study
- 3.5.1 Technical Feasibility
- 3.5.2 Economic Feasibility
- 3.5.3 Operational Feasibility
- 3.6 System Architecture
- 3.7 Data Flow Diagram (Level 0)
- 3.8 Data Flow Diagram (Level 1)
- 3.9 Data Flow Diagram (Level 2)
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04
Chapter 4 — System Design
- 4.1 Introduction
- 4.2 Use Case Diagram
- 4.3 Class Diagram
- 4.4 Sequence Diagram
- 4.5 Activity Diagram
- 4.6 ER Diagram
- 4.7 Database Schema
- 4.8 Table Structures
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05
Chapter 5 — System Implementation
- 5.1 Introduction
- 5.2 Development Environment
- 5.3 Tools and Technologies Used
- 5.4 Hardware Requirements
- 5.5 Software Requirements
- 5.6 Module-wise Implementation
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06
Chapter 6 — Testing
- 6.1 Introduction
- 6.2 Testing Strategy
- 6.3 Unit Testing
- 6.4 Integration Testing
- 6.5 System Testing
- 6.6 Test Cases
- 6.7 Bug Reports
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07
Chapter 7 — Results and Discussion
- All screenshots
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08
Chapter 8 — Conclusion and Future Enhancements
- 8.1 Conclusion
- 8.2 Future Enhancements
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09
Chapter 9 — References
Project's Overview
SecureVote is a final year project built with Python, Flask, SQLite, and TensorFlow for students who want a secure online election management web application. This final year project provides separate portals for administrators and voters, with voter registration, approval, elections, candidates, ballots, voting, results, audit logs, login history, and reports. A key feature of this final year project is face identity verification before vote submission using TensorFlow MobileNetV2 image embeddings and cosine similarity. Voters can enroll face images, view elections, cast one vote per election, and see published results. Admins can manage voters, elections, candidates, ballots, face data, fraud signals, notifications, results, CSV exports, and SQLite backups. SecureVote is suitable for a final year major project in Flask, cybersecurity, election systems, machine learning, and identity verification.
Login Credentials
Administrator
- Username:
admin - Password:
admin123 - Access:
/admin/*
Demo Voters
- Usernames:
voter1tovoter7 - Password:
voter123 - Access:
/voter/*after login
Related & Popular Reports
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- Admin dashboard for this final year project with voters, elections, votes, pending face tasks, completed elections, and audit snippets
- Admin profile update and password change
- Voter list, search, add, edit, delete, activate/deactivate, approve registration, and password reset
- Face data gallery management for voters
- Delete unclear face images and request re-upload
- Mark face enrollment complete
- Election creation and editing with title, description, start/end schedule, and ballot settings
- Election activation, deactivation, manual close, and deletion where allowed
- Ballot publishing and single-candidate-only option configuration
- Candidate add, edit, and delete with photo support
- Account control for pending, blocked, and locked users
- Face verification logs with score review and suspicious/reviewed status
- Fraud record viewing, resolving, flagging, and voting restriction support
- Cast vote monitoring with verification metadata
- Election result tallies, percentages, publish/hide controls, and CSV download
- Participation and verification-failure CSV reports
- In-app notification broadcast to all voters or selected users
- Audit log and login history
- SQLite database backup download
- Voter registration in this final year project with profile fields and optional face image
- Duplicate username, email, and voter ID validation
- Login using email or username and password
- Pending approval flow before full voter access
- Voter dashboard with profile summary, notifications, election status, and voted indicators
- Profile update for email, phone, and address
- Change password support
- Face enrollment with one or more images
- Face image preview list
- Re-upload response when admin requests clearer face data
- Open and all election listing
- Election detail view with candidates
- Ballot access during valid election window
- Webcam capture before voting
- Server-side face verification before vote submission
- Candidate selection and one-vote-per-election submission
- Published result viewing where allowed
- Logout functionality
- Public landing page included in this final year project
- Flask-Login session handling
- Werkzeug password hashing
- SQLite database with optional
DATABASE_URLoverride - Pillow-based image handling
- TensorFlow MobileNetV2 embeddings for face matching
- Cosine similarity threshold controlled by
FACE_MATCH_THRESHOLD - Configurable
MAX_FACE_VERIFICATION_RETRIESreserved for future stricter retry handling - In-app notifications stored in the database
- Seed data with admin, seven voters, elections, candidates, sample votes, and generated face images
- CSV exports for participation, verification failures, and election results
- Database backup download
- Suitable for final year project demo, viva, source code review, and report preparation
- Open the final year project root folder containing
run.pyandrequirements.txt. - Install dependencies:
pip install -r requirements.txt
Windows alternative:
python -m pip install -r requirements.txt - Optional: load demo data using:
python seed_data.py
Note: this drops all tables and recreates demo records. - Start the final year Flask project server:
python run.py - Open the application at:
http://127.0.0.1:5000 - Use these paths:
- Home:
/ - Login:
/auth/login - Voter registration:
/auth/signup - Admin dashboard:
/admin/dashboard - Voter dashboard:
/voter/dashboard
- Home:
- For testing face verification, allow browser camera permission and enroll real photos if live capture does not match generated demo images.
README Included
Setup Support Available
Administrator
- Username:
admin - Password:
admin123 - Access:
/admin/*
Demo Voters
- Usernames:
voter1tovoter7 - Password:
voter123 - Access:
/voter/*after login