Cold_Chain_Monitoring_System

ColdTrack - RSV Vaccine Cold Chain Monitoring System

IoT-enabled temperature monitoring system for RSV vaccine transportation with multi-dimensional freeze damage assessment

🎯 Project Overview

ColdTrack is an MSc capstone project addressing vaccine cold chain failures that compromise ~7% of vaccines globally. The system specifically targets RSV vaccine transportation, combining real-time monitoring with AI-powered freeze damage scoring.

Key Features

• ⚡ Sub-1.5s alert latency for critical temperature excursions
• 📊 Multi-dimensional freeze scoring (depth, duration, frequency)
• 🔍 RFID-based vaccine identification with dynamic thresholds
• 📍 GPS tracking for location-aware monitoring
• ☁️ Cloud-native architecture with AWS IoT Core
• 💰 ~£3 per unit cost target for scalability

🏗️ Architecture

ESP32 Device → AWS IoT Core → Lambda Functions → InfluxDB → Grafana
  (Layer 1)      (Layer 2)       (Layer 3)      (Layer 4)   (Layer 5)

Technology Stack

• Hardware: ESP32-WROOM-32, TMP112, DS18B20, NEO-6M GPS, RC522 RFID
• Connectivity: SIM800L (GSM/GPRS), MQTT over TLS 1.2
• Cloud: AWS IoT Core, Lambda, SNS
• Database: InfluxDB 2.x (time-series)
• Visualization: Grafana 10.x
• Languages: Python 3.11, C (ESP-IDF), Flux

🚀 Quick Start

Prerequisites

# Install dependencies
python3 --version  # 3.11+
docker --version   # 20.10+
aws --version      # 2.x

1. Clone & Setup

git clone https://github.com/Adhish-Rao2405/Cold_Chain_Monitoring_System.git
cd Cold_Chain_Monitoring_System
cp config/.env.example .env

2. Start Local Services

# Start InfluxDB + Grafana
docker-compose -f config/docker-compose.yml up -d

# Verify services
curl http://localhost:8086/health  # InfluxDB
curl http://localhost:3000          # Grafana

3. Setup AWS IoT Core

# Run automated setup
./scripts/setup_aws.sh

# This creates:
# - IoT Thing (CT-001)
# - Device certificates
# - IoT policy
# - IoT rule for Lambda

4. Deploy Lambda Functions

./scripts/deploy_lambda.sh

5. Run Device Simulator

cd device/simulator
pip install -r requirements.txt
python simulator.py

6. Access Grafana

Open http://localhost:3000

• Username: admin
• Password: admin

You should see live temperature data within 60 seconds! 🎉

📁 Project Structure

ColdTrack/
├── device/          # Device code (simulator + ESP32)
├── cloud/           # AWS infrastructure (IoT, Lambda)
├── database/        # InfluxDB schemas & queries
├── visualization/   # Grafana dashboards
├── scripts/         # Setup & deployment scripts
├── tests/           # Test suite
└── docs/            # Documentation

See PROJECT_STRUCTURE.md for detailed structure.

🧪 Testing

# Unit tests
pytest tests/unit/

# Integration tests
pytest tests/integration/

# Test MQTT connection
./scripts/test_connection.sh

📊 Monitoring

• Grafana Dashboard: http://localhost:3000
• InfluxDB UI: http://localhost:8086
• AWS IoT Console: https://console.aws.amazon.com/iot
• Lambda Logs: aws logs tail /aws/lambda/ColdTrack-Process --follow

🔧 Configuration

Environment Variables

Copy .env.example to .env and configure:

# AWS Configuration
AWS_REGION=eu-west-2
AWS_ACCOUNT_ID=your_account_id

# InfluxDB Configuration
INFLUX_URL=http://localhost:8086
INFLUX_TOKEN=your_token
INFLUX_ORG=coldtrack
INFLUX_BUCKET=sensors

# Alert Thresholds
TEMP_MIN=2.0
TEMP_MAX=8.0
FREEZE_ALERT_THRESHOLD=0.0

Device Configuration

Edit device/simulator/config.json:

{
  "device_id": "CT-001",
  "mqtt_endpoint": "xxxxx.iot.eu-west-2.amazonaws.com",
  "topic": "coldtrack/sensors/CT-001/data",
  "publish_interval": 60,
  "temp_range": [2.0, 8.0]
}

📚 Documentation

• Architecture Details
• API Reference
• Deployment Guide
• Troubleshooting

🎯 Development Roadmap

Phase 1: Core System (January 2026) ✅

• AWS IoT Core setup
• Device simulator
• Lambda data processor
• InfluxDB integration
• Basic Grafana dashboard

Phase 2: Enhanced Features (February 2026) 🔄

• Multi-device support
• GPS tracking integration
• RFID vaccine identification
• Advanced freeze scoring algorithm
• Email/SMS alerts via SNS

Phase 3: Hardware Integration (March 2026) 📝

• ESP32 firmware
• Sensor integration (TMP112, DS18B20)
• GSM connectivity (SIM800L)
• Power optimization
• Field testing

Phase 4: Testing & Refinement (April 2026) 📝

• End-to-end testing
• Performance optimization
• Documentation completion
• Final presentation preparation

👥 Team

• Adhish Rao - Hardware & Electronics
• Paul - AI/ML & Freeze Scoring Algorithm
• Louis - Wireless Communication & Cloud Integration
• Kevin - Software Development

Supervisor: Dr. Akin Delibasi
Institution: University College London
Course: MSc Designing Sensor Systems
Deadline: April 2026

📄 License

This project is part of academic coursework at UCL.

🙏 Acknowledgments

• UCL Department of Computer Science
• Dr. Akin Delibasi for project supervision
• AWS Educate for cloud credits
• Open-source community for tools and libraries

📞 Contact

For questions or collaboration:

• GitHub: @Adhish-Rao2405
• Project Repository: ColdTrack

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