AI-Driven NEET UG Medical Admission Data Entry

# Project Requirement Document ## AI-Based Automated NEET UG Medical Admission Prediction Platform ### Project Overview We are developing a nationwide AI-powered NEET UG Medical Admission Prediction & Counselling Platform for MBBS admissions across India. The goal is to create a highly automated system that can: * Collect counselling data automatically * Process and standardize data from different states * Generate accurate college prediction * Forecast expected closing ranks * Provide admission probability * Reduce manual data entry dependency The system should initially use past 3 years’ counselling data and later automatically support future counselling years with minimal human intervention. --- # IMPORTANT OBJECTIVE The system must be designed so that: ✅ After initial setup and training ✅ One admin/operator can manage the entire platform ✅ No large freelancer/data-entry team should be required in future The platform should automate: * Data collection * File downloading * Data extraction * Data normalization * Validation * Cutoff generation * Seat matrix processing * Forecast preparation --- # Main Platform Goals ## 1. Automated Data Collection System should automatically collect: * MCC counselling data * State counselling data * Seat matrix * Round-wise allotment results * Cutoff files * Vacancy data from official counselling websites. --- # 2. Universal Data Processing System Different states provide data in different formats: * Excel * PDF * Candidate allotment lists * Closure reports * HTML tables The platform must automatically convert all formats into one universal standardized structure. --- # 3. AI-Based Prediction System The system should: * Analyze previous years’ trends * Compare seat changes * Detect cutoff movement * Forecast expected closing rank * Calculate admission probability for each: * College * Category * Quota * Round --- # 4. Full College Recommendation Engine Student inputs: * AIR * Category * State * Budget * Domicile * Preferences System outputs: * Safe colleges * Moderate colleges * Dream colleges * Best counselling round strategy * Expected admission probability --- # 5. Premium Counselling Dashboard Dashboard should include: * Student management * Prediction reports * Counselling strategy * Saved preferences * Round-wise tracking * Live cutoff movement * Vacancy tracking --- # AUTOMATION REQUIREMENTS ## A. Auto Scraping System (VERY IMPORTANT) System should automatically: * Visit counselling websites * Detect latest files * Download files * Store raw files * Trigger parser automatically Supported sources: * MCC * State counselling authorities * AIQ * Deemed universities * Government medical counselling websites --- ## B. Parser Engine Separate parser modules should be created for each authority. Example: * MCC parser * Gujarat parser * Karnataka parser * Rajasthan parser The parser should: * Read PDFs/Excel files * Extract counselling data * Identify categories/quota/round * Generate closing ranks automatically --- ## C. Normalization Engine The system must standardize: * Categories * Quotas * Rounds * College names * Course names Example: * GEN → OPEN * SEBC → OBC * AIQ → All India Quota --- ## D. Validation Engine System should automatically detect: * Duplicate entries * Invalid ranks * Missing categories * Incorrect college mapping * Wrong scores Admin should receive validation alerts. --- # FUTURE-READY REQUIREMENT The system must NOT be hardcoded only for current years. It should support: * Future counselling years * New colleges * New quotas * Reservation changes * Seat increases * New states * Additional courses (BDS/BAMS/BHMS later) without major redevelopment. --- # REQUIRED MASTER DATABASE STRUCTURE The platform should maintain: * College master database * Course master database * Category mapping database * Quota mapping database * Seat matrix database * Cutoff history database * Vacancy movement database --- # PREDICTION ENGINE REQUIREMENTS Prediction engine should: * Use past 3+ years data * Analyze historical trends * Compare seat matrix changes * Detect competition changes * Forecast expected closing ranks Outputs should include: * Expected closing AIR * Admission probability % * Recommended counselling round * Safe/Moderate/Dream classification --- # ADMIN PANEL REQUIREMENTS Admin dashboard should allow: * File upload * Parser management * Error logs * Validation review * Manual correction * College mapping * Trend analysis * Prediction override * Seat matrix management The system should minimize manual work as much as possible. --- # SCALABILITY REQUIREMENT Initial Phase: * MBBS only Future Expansion: * BDS * BAMS * BHMS * BUMS * Veterinary * AYUSH counselling without rebuilding the architecture. --- # RECOMMENDED TECH STACK ## Backend * Python FastAPI ## Database * PostgreSQL ## Scraping * Playwright + BeautifulSoup ## Data Processing * Pandas ## Queue System * Celery + Redis ## Frontend * [login to view URL] / React ## Cloud Storage * AWS S3 / DigitalOcean Spaces --- # IMPORTANT DEVELOPMENT APPROACH The system should be built as: * Data-first architecture * Modular parser system * Automation-focused platform * AI-enhanced prediction engine NOT as a simple static predictor website. --- # FINAL GOAL Build a scalable and highly automated NEET UG counselling intelligence platform where: * One trained operator/admin can manage the system * Manual data entry dependency is minimal * Future counselling years can be processed automatically * Prediction quality continuously improves with data * Platform becomes a premium counselling and admission solution for students across India

Project ID: 40450085