01 Synopsis
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- Problem statement & objectives
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Complete BSc final-year project report with documentation, diagrams and viva-ready structure. Instant PDF & Word download — plagiarism-free and faculty-aligned.
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01 Synopsis
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02 Pre Defined Project Report
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03 Customized Report
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04 Originality Reviewed
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Abstract
Table of Content
Introduction
Problem Statement
Existing System
Proposed System
Objectives
System Architecture
Major Functional Modules
Hardware Requirements
Software Requirements
Future Enhancement
Conclusion
References
Abstract
Table of Content
Chapter 1 — Introduction
Chapter 2 — Literature Review / System Study
Chapter 3 — System Analysis
Chapter 4 — System Design
Chapter 5 — System Implementation
Chapter 6 — Testing
Chapter 7 — Results and Discussion
Chapter 8 — Conclusion and Future Enhancements
Chapter 9 — References
Unified Citizen Grievance Prediction System is a Python Flask based final year project developed for managing civic complaints, citizen grievances, department assignment, complaint tracking, reports, and AI-powered issue prediction. This major project includes a public website, citizen portal, and admin console. Citizens can register, log in, submit complaints, track complaint status, upload evidence, view notifications, download receipts, check area-wise risk predictions, update profile, change password, and submit feedback after resolution. Admins can manage departments, categories, areas, wards, complaint types, citizens, complaints, training data, ML predictions, reports, notifications, FAQs, site content, feedback, backup/restore, profile, and password settings. This citizen grievance prediction system source code is suitable for students who need a final year project, major project, minor project, source code, and project report based on Flask, SQLite, machine learning, and civic issue management.
Admin Account
adminadmin123[email protected]Demo Citizen Accounts
All demo citizens use password:
password123
Demo users:
john_doeOpen project folder:
cd "Unified Citizen Grievance Prediction System"
Create virtual environment:
python -m venv venv
Activate virtual environment on Windows:
venv\Scripts\activate
Activate virtual environment on Linux/macOS:
source venv/bin/activate
Install dependencies:
pip install -r requirements.txt
Seed database with demo data:
python seed.py
Start application:
python app.py
Alternative run command:
python run.py
Open public landing page:
http://localhost:5000
http://localhost:5000/login
http://localhost:5000/user/dashboard
http://localhost:5000/admin/dashboard
Admin Account
adminadmin123[email protected]Demo Citizen Accounts
All demo citizens use password:
password123
Demo users:
john_doe