AI-Powered IQAC Academic Intelligence & Accreditation Monitoring System

Full MERN project inside one workspace with:

frontend (React + Tailwind + Chart.js)
backend (Node + Express + MongoDB + JWT+LLM)

Features Implemented

Core Roles and Login

Admin (IQAC), HOD, Faculty, Student roles
JWT authentication
Role-based route protection

Academic Monitoring

Student profile and semester-wise metrics
CGPA trend, attendance pattern, backlog count
Risk prediction engine (LOW, MEDIUM, HIGH)

Department Monitoring

Department creation and listing
Department analytics (pass%, avg CGPA, backlog rate, placement rate)
Placement and achievement data entry

Faculty Inputs

Upload marks
Upload attendance
Add research/publication records

Accreditation Intelligence

Store accreditation evidence for NAAC/NBA/AUDIT
Filter by criterion/department/year/status
Readiness score with missing items

Automated Reports

Report generation endpoint with PDF/Excel export
Supported types:
- Student Progress
- Department Performance
- CGPA Distribution
- Backlog Analysis
- Placement
- Faculty Contribution
Report history log

Dashboard and Demo Flow

Faculty Panel for marks and attendance upload
Admin Dashboard with:
- institutional analytics
- department comparison chart
- risk distribution chart
- report download buttons
Student dashboard with CGPA trend and risk badge

Project Structure

IQAC/
  backend/
    src/
      config/
      controllers/
      middleware/
      models/
      routes/
      services/
      utils/
  frontend/
    src/
      api/
      components/
      context/
      layouts/
      pages/
      styles/

Setup

1) Backend

cd backend
npm install

Create .env using .env.example as template.

Update .env:

PORT=5000
MONGO_URI=mongodb://127.0.0.1:27017/iqac_monitoring
JWT_SECRET=replace_with_strong_secret
JWT_EXPIRES_IN=1d

Run backend:

npm run dev

Seed demo data:

npm run seed

2) Frontend

cd frontend
npm install
npm run dev

Create .env using .env.example as template.

Frontend runs on http://localhost:5173.

Demo Credentials (after seed)

Password for all:

Admin@123

Users:

Admin: admin@iqac.edu
HOD: hod.cse@iqac.edu
Faculty: faculty.cse@iqac.edu
Student: ravi@student.iqac.edu

Key API Endpoints

POST /api/auth/login
POST /api/auth/register (admin only)
GET /api/analytics/overview
GET /api/analytics/department-comparison
GET /api/analytics/risk-students?risk=HIGH
POST /api/faculty/students/:studentId/marks
POST /api/faculty/students/:studentId/attendance
POST /api/reports/generate
GET /api/accreditation/readiness?type=NAAC

Notes

Frontend build is validated.
Backend requires MongoDB connection configured in .env.
This is a hackathon-ready foundation and can be extended with advanced ML models, notifications, and full audit trails.

IQAC System — Complete Project Analysis

AI-Powered Internal Quality Assurance Cell Academic Intelligence & Accreditation Monitoring System

1. High-Level Architecture

graph TB
    subgraph Frontend["Frontend (Vite + React 18)"]
        LP[Landing Page]
        Login[Login Page]
        Admin[Admin Dashboard]
        HOD[HOD Dashboard]
        Faculty[Faculty Dashboard]
        Student[Student Dashboard]
    end
    subgraph Backend["Backend (Express 4 + Node.js)"]
        API[REST API :5000]
        Auth[JWT Auth Middleware]
        Controllers[9 Controllers]
        Services[LLM + Report Services]
    end
    subgraph Data["Data Layer"]
        MongoDB[(MongoDB Atlas<br/>iqac_monitoring)]
        AttDB[(MongoDB Atlas<br/>attendance_patterns)]
        Ollama[Ollama Mistral LLM<br/>localhost:11434]
    end
    Frontend -->|axios + fetch SSE| API
    API --> Auth --> Controllers --> Services
    Controllers --> MongoDB
    Controllers --> AttDB
    Services --> Ollama

2. Technology Stack

Layer	Technology	Version
Runtime	Node.js	22.x
Backend	Express.js	4.19
Frontend	React	18.3
Bundler	Vite	5.3
Styling	TailwindCSS	3.4
Database	MongoDB Atlas (Mongoose 8.5)	—
LLM	Mistral via Ollama	local
Auth	JWT (jsonwebtoken)	9.0
Charts	Chart.js 4 + Recharts 3	—
PDF	PDFKit	0.15
Excel	ExcelJS	4.4
Security	Helmet, bcryptjs, CORS	—

3. Backend Architecture

3.1 Database Connections

Two separate MongoDB Atlas clusters managed via mongoose.createConnection():

Connection	Database	Purpose
`mainDB`	`iqac_monitoring`	All core data (students, marks, departments, etc.)
`attendanceDB`	`attendance_patterns`	Secondary attendance pattern analysis

3.2 Models (18 Mongoose Schemas)

Model	Key Fields	Relationships
Student	`rollNo`, name, `email`, `currentSemester`, `batch`, `riskLevel`, `metrics[]` (semester SGPA/CGPA/backlogs/attendance), `feeDetails`	→ Department
Department	name, `code`, `vision`, `mission`	→ User (HOD)
User	name, `email`, `password`, `role` (admin/hod/faculty/student), `facultyProfile`, `registrationNumber`	→ Department, → Student
Mark	`subjectCode`, `subjectName`, `semester`, `internal`, `external`, `total`, `passed`	→ Student, → User (faculty), → Section
Attendance	`semester`, `academicYear`, `totalClasses`, `attendedClasses`, `percentage`, `subjects[]`	→ Student, → User
Placement	`academicYear`, `totalEligible`, `totalPlaced`, `highestPackageLPA`, `medianPackageLPA`, `majorRecruiters[]`	→ Department
Research	`title`, `publicationType` (Journal/Conference/Patent/Book Chapter), `journalOrConference`, `publishedOn`	→ Department, → User (faculty)
AccreditationItem	`title`, `body`, `type` (NAAC/NBA/AUDIT), `criterion`, `completed`, `evidenceUrl`	→ Department, → User
Achievement	`title`, `category` (Faculty/Student/Department), `level` (Institute/State/National/International)	→ Department
ReportLog	`reportType`, `format` (PDF/EXCEL), `filters`	→ User
Section	Section management	→ Department
DepartmentStat	Department statistics	→ Department
Faculty	Faculty-specific data	—
FacultyAchievement	Faculty achievement records	—
StudentAchievement	Student achievement records	—
StudentActivity	Student event participation	—
TeachingAssignment	Teaching load tracking	—
Announcement	System announcements	—

3.3 API Routes (9 Route Files, ~50+ Endpoints)

Route File	Base Path	Auth	Key Endpoints
authRoutes	`/api/auth`	Public + Protected	`POST /login`, `POST /public-signup`, `GET /me`
studentRoutes	`/api/students`	admin, hod	CRUD, filters, dashboard, metrics
departmentRoutes	`/api/departments`	admin, hod	CRUD, analytics, placements, achievements
facultyRoutes	`/api/faculty`	faculty, hod	Marks upload, attendance, research
analyticsRoutes	`/api/analytics`	admin, hod, faculty	Overview, department comparison, risk students
reportRoutes	`/api/reports`	admin, hod	Generate PDF/Excel, history
accreditationRoutes	`/api/accreditation`	admin, hod	Items CRUD, readiness score
aiRoutes	`/api/ai`	admin, hod, faculty	8 AI jobs + streaming search
adminRoutes	`/api/admin`	admin	User management

3.4 Controllers (9 Files)

Controller	Purpose
authController	Login, signup, JWT token generation, `GET /me`
studentController	Student CRUD, dashboard data, semester metrics, filtering
departmentController	Department CRUD, analytics, placement data, achievements
facultyController	Marks entry, attendance tracking, research publication management
analyticsController	KPI overview, department ranking, risk distribution
reportController	PDF/Excel report generation, report history logging
accreditationController	NBA/NAAC accreditation item management, readiness calculation
aiController	All 8 AI report controllers + streaming SSE search
adminController	User management (admin-only)

3.5 Services (2 Files)

Service	Purpose	Key Features
llmService	All Mistral LLM interactions	8 specialized prompt functions + NL query, in-memory cache (5 min TTL), `num_predict:80-200`, `temperature:0.3`
reportService	PDF and Excel file generation	PDFKit for PDF, ExcelJS for Excel spreadsheets

3.6 Security & Middleware

Component	Implementation
Authentication	JWT Bearer tokens via protect() middleware
Authorization	Role-based via authorize("admin","hod",...) — 4 roles: admin, hod, faculty, student
Password Hashing	bcryptjs with salt round 10
Security Headers	Helmet.js
CORS	Open CORS for dev
Request Logging	Morgan (dev format)
Error Handling	`express-async-errors` + global error handler
Body Limit	5 MB JSON limit

4. LLM Integration (Mistral via Ollama)

4.1 Architecture

sequenceDiagram
    participant U as User (Browser)
    participant API as Express API
    participant DB as MongoDB
    participant LLM as Ollama Mistral

    U->>API: POST /api/ai/search-stream
    API->>DB: Promise.all([Students, Departments, ...])
    DB-->>API: Raw data
    API->>API: Aggregate & summarize data
    API->>LLM: POST /api/generate (stream: true)
    loop Token by token
        LLM-->>API: { response: "word" }
        API-->>U: SSE: data: {"token": "word"}
    end

4.2 The 8 AI Jobs

Job	Function	Input Data	Output
1	Student Progress Analysis	Risk levels, CGPA, attendance, backlogs	4-sentence formal analysis
2	Department Performance	Dept scores, CGPA, pass%, placement%	NBA compliance assessment
3	CGPA Distribution	Distribution bands, NBA threshold	3-sentence pattern analysis (cached)
4	Backlog Analysis	Clean pass rate, worst dept/semester	Severity + intervention plan
5	Placement Forecast	Placement rates, packages, recruiters	Trend forecast + recommendations
6	Faculty Contribution	Publications, types, per-faculty ratio	NBA Criterion 4 compliance
7	Accreditation Readiness	NBA/NAAC scores, missing items	Audit readiness verdict (cached)
8	Natural Language Search	Full DB summary as context	2-sentence factual answer

4.3 Performance Optimizations Applied

Optimization	Impact
`num_predict: 80-200` tokens	Forces short, fast responses
`temperature: 0.3`	Consistent, focused output
`Promise.all()` for DB queries	3-5x faster data loading
`.lean()` on all Mongoose queries	Plain JS objects — no Mongoose overhead
In-memory cache (5 min TTL)	Instant repeat queries for Jobs 3 & 7
SSE streaming for search	First word appears in 1-2 seconds
Short prompts (~500 chars)	Reduced prompt processing time

5. Frontend Architecture

5.1 Routing & Role-Based Access

Route	Page	Allowed Roles
`/`	Landing Page	Public
`/auth`	Login Page	Public
`/home`	Home Page	All authenticated
`/admin`	Admin Dashboard	admin
`/hod`	HOD Dashboard	hod
`/faculty`	Faculty Dashboard	faculty, hod, admin
`/student`	Student Dashboard	student

5.2 Pages (8)

Page	Key Features
LandingPage	Public intro page
LoginPage	Email/password login form
AdminDashboard	KPI cards, charts, AI search (streaming), report generation
HodDashboard	Department-scoped analytics
FacultyDashboard	Marks/attendance entry, research
StudentDashboard	Personal performance view
HomePage	Role-based landing
NotFoundPage	404 handler

5.3 Components (21)

Charts: DepartmentChart, DepartmentComparisonChart, RiskChart, RiskDistributionChart, RiskDoughnut, SectionComparisonChart, SectionPerformanceChart, FacultyRiskChart, SafeChartContainer
UI: StatCard, StatsCards, FacultyStatsCards, TopStudentsTable, Sidebar, AdminSidebar, FacultySidebar
Management: AddFacultyDrawer, AttendanceManager, FacultyAchievements, FacultyProfile
Auth: ProtectedRoute

6. Data Flow Summary

flowchart LR
    subgraph Input
        JSON[Seed JSON Files]
        Faculty[Faculty Entry]
        Admin[Admin Upload]
    end
    subgraph Storage
        Mongo[(MongoDB Atlas)]
    end
    subgraph Processing
        Controllers[Controllers]
        LLM[Mistral LLM]
    end
    subgraph Output
        Dashboard[React Dashboards]
        PDF[PDF Reports]
        Excel[Excel Reports]
        AI[AI Analysis]
    end
    JSON --> Mongo
    Faculty --> Mongo
    Admin --> Mongo
    Mongo --> Controllers
    Controllers --> LLM
    Controllers --> Dashboard
    LLM --> AI
    Controllers --> PDF
    Controllers --> Excel

7. Database Statistics (Live)

Collection	Count
Students	90
Departments	3 (CSE, ECE, MECH)
Users	Multiple (admin, hod, faculty, student roles)
Marks	Per-student per-subject records
Placements	Per-department per-year
Research	Faculty publications
AccreditationItems	NBA + NAAC criteria

8. Test Coverage

A comprehensive 13-suite, 76-test test suite exists at testAll.js:

Suite	Tests	Coverage
Pre-flight Checks	7	Server, DB, Ollama health
Authentication	9	Login, signup, JWT, roles
Student API	6	CRUD, filters, dashboard
Department API	3	CRUD, analytics, placements
Analytics API	5	KPIs, comparison, risk
Accreditation API	5	Items, readiness, filters
LLM Data Aggregation	8	Data pipeline verification
LLM Job Tests	14	All 8 Mistral jobs
LLM Accuracy	5	Answers match DB values
Cache Tests	3	Set/get/clear verification
Load Tests	1	Sequential performance
NL Search	10	Natural language questions
Security	2	Role enforcement

Last run result: 75/76 passed (99% success rate)

9. Environment Configuration

Variable	Purpose
`PORT`	Backend port (5000)
`MONGO_URI`	Main database connection
`DB_PASSWORD`	MongoDB Atlas password
`ATTENDANCE_MONGO_URI`	Secondary attendance DB
`JWT_SECRET`	Token signing secret
`JWT_EXPIRES_IN`	Token expiry (1 day)

10. Key Project Strengths

Full-stack MERN with clean separation of concerns
Role-based access control at route, controller, and frontend level
Real LLM integration with Mistral for intelligent analysis
Live SSE streaming for responsive AI search
NBA/NAAC accreditation tracking with readiness scoring
Multi-format report generation (PDF + Excel)
Comprehensive test suite with 76 tests across 13 categories
Performance-optimized DB queries with Promise.all() and .lean()
In-memory caching for expensive LLM calls
Dual database architecture for specialized data stores

11. Areas for Improvement

Area	Current State	Recommendation
LLM Speed	15-20s per query (local Mistral)	Use cloud GPU or smaller model (e.g., `mistral:7b-instruct-v0.2-q4_0`)
JWT Secret	Hardcoded weak value	Generate a strong random secret
Error Logging	Console-only	Add structured logging (Winston/Pino)
API Pagination	Missing on list endpoints	Add `?page=&limit=` to student/mark queries
Input Validation	Basic Mongoose validation	Add express-validator for request body
File Uploads	No evidence file upload	Add multer for accreditation evidence docs
Rate Limiting	None	Add express-rate-limit for AI endpoints
Test Automation	Manual `node` command	Add to CI/CD pipeline

Name		Name	Last commit message	Last commit date
Latest commit History 27 Commits
New folder		New folder
backend		backend
frontend		frontend
.gitignore		.gitignore
README.md		README.md
anti_gravity_audit.md		anti_gravity_audit.md
package-lock.json		package-lock.json

Folders and files

Latest commit

History

Repository files navigation

AI-Powered IQAC Academic Intelligence & Accreditation Monitoring System

Features Implemented

Core Roles and Login

Academic Monitoring

Department Monitoring

Faculty Inputs

Accreditation Intelligence

Automated Reports

Dashboard and Demo Flow

Project Structure

Setup

1) Backend

2) Frontend

Demo Credentials (after seed)

Key API Endpoints

Notes

IQAC System — Complete Project Analysis

1. High-Level Architecture

2. Technology Stack

3. Backend Architecture

3.1 Database Connections

3.2 Models (18 Mongoose Schemas)

3.3 API Routes (9 Route Files, ~50+ Endpoints)

3.4 Controllers (9 Files)

3.5 Services (2 Files)

3.6 Security & Middleware

4. LLM Integration (Mistral via Ollama)

4.1 Architecture

4.2 The 8 AI Jobs

4.3 Performance Optimizations Applied

5. Frontend Architecture

5.1 Routing & Role-Based Access

5.2 Pages (8)

5.3 Components (21)

6. Data Flow Summary

7. Database Statistics (Live)

8. Test Coverage

9. Environment Configuration

10. Key Project Strengths

11. Areas for Improvement

About

Resources

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Uh oh!

Contributors

Uh oh!

Languages

Packages