Smart Study Scheduler (Browser-Based AI Planner)

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  Home page(The Home Page lets users add subjects, manage them, and quickly generate daily or weekly study plans in a simple way.)

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  Add Subject page

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  genrate today'plan

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  genrate topics to study today

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  after run demo

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  whole demo of an all fetaures

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  delete the subjects

Inspiration

Students often struggle to decide what to study first, how much time to spend, and how to balance multiple subjects before exams. Many tools are either too complex, require internet access, or don’t adapt to urgency. Goal: Build a simple, fast, distraction-free planner that works entirely offline while still feeling “smart.”

What it does

Smart Study Scheduler helps students turn raw exam information into a clear, actionable study plan.

Key Functions: Add subjects with exam date, difficulty, and topics. Automatically prioritizes based on urgency + workload. Generates: ✅ Full Study Plan ✅ Today's Tasks ✅ Weekly Schedule (10-hour/day cap) Runs 100% in the browser — no login, no internet required. Saves data using localStorage (key: ss_subjects) for persistence.

How we built it

We designed it as a lightweight frontend-only application.

Tech Stack: HTML → Structure and UI components CSS → Clean, responsive layout Vanilla JavaScript → Logic and state management localStorage → Data persistence (no backend) Core Logic:

A rule-based heuristic algorithm calculates study weight using: 📅 Days left to exam (urgency) 📚 Number of topics (workload) ⚙️ Difficulty level (effort multiplier) Outputs a deterministic, optimized study distribution.

Challenges we ran into

1.Designing a system that feels “intelligent” without using ML or APIs. 2.Balancing schedules so students don’t get overloaded (>10 hrs/day). 3.Managing state persistence + undo functionality purely on the client side. 4.Creating smooth UX (loading overlays, progress feedback) without frameworks.

Accomplishments that we're proud of

Built a fully offline AI-like planner — no external services needed. ✅ Achieved zero-dependency architecture (no libraries/frameworks). ✅ Implemented dynamic scheduling logic that adapts to real constraints. ✅ Added thoughtful UX features: Bulk delete + undo toast Demo data seeding Loading progress simulation ✅ Fast, private, and works even in low-connectivity environments.

What we learned

1.Heuristic algorithms can solve real problems without heavy AI. 2.Good UX (feedback, undo, progress indicators) is just as important as logic. l3.ocalStorage can power surprisingly capable apps when structured properly. 4.Simplicity + reliability often beats feature-heavy solutions for students.

What's next for Smart Study Scheduler (Browser-Based AI Planner)

Planned Enhancements:

✏️ Editable subject rows (remembered changes in-place). 📊 Study analytics (time distribution & completion tracking). 🔁 Longer undo history + autosave timestamps. 📱 Improved mobile-first interface.

Future AI Integration (Optional Upgrade): 1.Add a secure backend + LLM API to provide: 2.Personalized study strategies 3.Natural-language explanations 4.Adaptive rescheduling when plans change

Vision: Keep the app fast and offline-first, while offering an optional AI-enhanced mode for deeper personalization.

Built With

• browser
• css
• dom
• heuristic-based-ai
• html
• javascript
• localstorage