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OptiCare

Inefficient bed management, overcrowded OPDs, and staff tracking issues cause delays. Outdated, manual systems further hinder hospital operations.

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Description

OptiCare – Smart Hospital Management System

Hack KRMU 4.0 | Team: Syntax Squad , Team ID - 20

Team Members: Ayush Rai, Deepanshi Gupta, Himanshu, Mayank Kumar

Problem Statement:

Hospitals face inefficiencies due to:

  1. Bed Management Delays: Lack of real-time occupancy updates.

Overcrowded OPDs & ERs: Ineffective queue management leads to long wait times.

  1. Staff Tracking Issues: Difficulty in locating doctors and nurses in real time.

Outdated Systems: Reliance on manual, paper-based processes.

Proposed Solution: OptiCare

  1. IoT-Enabled Bed Monitoring: Sensors update bed availability in real-time.

AI-Based Queue Management: Smart vision systems optimize OPD flow.

Staff Presence Tracking: Bluetooth Beacons monitor on-duty doctors/nurses.

  1. Predictive Resource Allocation: ML models forecast patient influx and adjust resources dynamically.

Methodology:

  1. Data Collection & Integration: IoT sensors (NFC, Bluetooth Beacons), ESP32-CAM for crowd monitoring.

  2. AI & ML Implementation: Predict bed availability, patient influx, and optimize queue congestion.

  3. System Development & Automation: A centralized dashboard for real-time hospital monitoring.

  4. Testing & Optimization: AI models are refined using real-world hospital data.

  5. Deployment & Scaling: Seamless integration into existing hospital infrastructure.

  6. Prototype & Implementation Strategy:

  • NFC Tags for real-time bed tracking.

  • Bluetooth Beacons for staff monitoring.

  • AI-Powered ESP32 Camera for crowd detection.

  • Dashboard Development for real-time data visualization.

  • Testing & Optimization before full-scale hospital deployment.

Conclusion:

OptiCare is a smart hospital management system that leverages IoT and AI for efficient patient flow, real-time resource tracking, and predictive healthcare management to reduce wait times, improve staff allocation, and optimize hospital operations.

Progress During Hackathon

60

Tech Stack

React
Next
Python
Node
firebase
mongodb
iot devices
arduino ide

Fundraising Status

1. Pre-Seed (₹25L - ₹1 Cr) → MVP development, pilot testing in 5-10 hospitals. Covers IoT devices, software, and cloud setup. 2. Seed Round (₹1 Cr - ₹5 Cr) → Expansion to 50+ hospitals, large-scale device deployment & hospital onboarding. 3. Series A (₹10 Cr+) → Nationwide scaling, 100+ hospitals, deeper hospital integrations, and advanced features. Why Invest? 1. High demand: Solving OPD & bed management issues. 2. Scalable SaaS model: Recurring revenue from hospitals. 3. Early traction: Starting with small hospitals, then scaling.

Team Leader
Aarai70746
Sector
AIOther