Study-AI (Edu Pilot) is a premium, dark-themed Academic Tracking and Performance Dashboard tailored specifically for B.Tech CSE students. Designed to streamline academic workflows, track consistency, and simulate academic predictions, the application combines a modern Cyber-Slate & Neon Blue UI with a robust Java Servlet backend and MySQL database.
- Subject Portfolio Manager: Register academic courses, select perceived difficulty (1–5 scale), log current accuracy/mastery metrics, and schedule final exam targets.
- Daily Consistency Heatmap: A custom 30-day contribution grid (modeled on GitHub's design) color-coding daily study habits.
- AI Success Predictor: Calculate score trends and estimate success probabilities based on target scores and daily study durations.
- Performance Metrics Charting: Dynamic double-bar graphs comparing mastery vs. accuracy across all courses using Chart.js.
- Dynamic AI Insight Engine: Custom, automated study recommendations prioritizing weak spots depending on accuracy scores.
The interface is built using a customized dark-mode layout:
- Color Palette: Sleek slate backgrounds (
#0f172a), deep navy sidebars, and high-contrast electric neon highlights (#38bdf8,#10b981,#f43f5e). - Typography: Clean, high-legibility layout using Google's Inter sans-serif font family.
- UI Components: Neon-glow buttons, smooth hover translations, frosted cards, and subtle micro-animations for an interactive developer experience.
project-root/
│
├── .github/
│ └── workflows/
│ └── build.yml # GitHub Actions CI Workflow
│
├── assets/
│ └── branding/ # Graphics, logos, and screenshots
│
├── config/
│ └── schema.sql # SQL database initialization script
│
├── docs/
│ ├── ARCHITECTURE.md # Mermaid dataflow diagrams and design notes
│ ├── INSTALLATION.md # Step-by-step local setup guides
│ └── FAQ.md # Common errors and database troubleshooting
│
├── src/
│ └── main/
│ ├── java/
│ │ └── com/
│ │ └── studyplanner/ # Recovered Java Servlet and Model sources
│ │
│ └── webapp/
│ ├── css/
│ │ └── style.css # Unified custom CSS stylesheet
│ ├── includes/
│ │ └── sidebar.jsp # Shared dynamic sidebar fragment
│ └── WEB-INF/
│ └── web.xml # Servlet configurations mapping
│
├── LICENSE # Apache-2.0 open-source license
├── pom.xml # Maven dependency descriptor
└── README.md # Main project overview
For a detailed look at sequence flows and classes, view docs/ARCHITECTURE.md.
Ensure you have MySQL running. Create and seed the tables using:
mysql -u root -p < config/schema.sqlNote: Make sure to check docs/FAQ.md if you encounter column name or connection anomalies.
Set environment overrides for custom user configurations, or let the app fallback to the standard credentials:
DB_URL(default:jdbc:mysql://localhost:3306/ai_study_planner)DB_USER(default:root)DB_PASSWORD(default:231912)
Build the package using Maven:
mvn clean packageDeploy the generated target/ai-study-planner.war file directly into your Apache Tomcat webapps/ folder, start the server, and navigate to:
http://localhost:8080/ai-study-planner
For complete setup assistance, check the docs/INSTALLATION.md.
- Language & Core: Java (JDK 17/21/25), JSP, Jakarta Servlets 6.0
- Build Tool: Apache Maven
- Database: MySQL, JDBC Driver 8.3.0
- Design & UI: CSS3 custom vars, FontAwesome Icons, Google Inter Web Fonts, Chart.js Charts
- True AI/ML Integrations: Integrate a Python Flask/FastAPI microservice running Linear Regression models to evaluate student success rates mathematically.
- Authentication & Sessions: Add secure Multi-User Authentication using bcrypt password hashing.
- Reminders & Push Notifications: Integrate email triggers alerting students on upcoming exam dates.
- Pomodoro Timer Integration: Add an interactive sidebar stop-watch tab tracking real-time studies directly updating the activity heatmap.
- Concept & Core Logic: Originally designed by Sanya Jaiswal.
- Refactoring & Modernization: Restructured and documented using Antigravity AI coding standards.
This project is open-source and available under the terms of the Apache License 2.0.