Cold Chain Monitoring

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source platform for IoT temperature tracking, excursion alerting, and compliance documentation across pharmaceutical, food, and vaccine cold chains.

Cold Chain Monitoring is a candidate platform for ingesting real-time sensor data, managing temperature excursions, and producing regulator-ready documentation for shippers, 3PLs, pharma manufacturers, and food operators. It aims to close the gap between expensive enterprise-grade incumbents and lightweight tools that lack pharmaceutical-grade compliance.

Why Cold Chain Monitoring?

Incumbents like Sensitech, Controlant, and Elpro deliver pharma-grade compliance but rely on hardware lock-in and enterprise contracts with no SMB-friendly tier.
Real-time tracker services such as Tive charge $3–5 per device per day, making continuous monitoring expensive at scale.
Most platforms detect excursions reactively; predictive excursion forecasting hours before a breach is rare across the market.
Data is siloed per vendor — no incumbent supports EPCIS 2.0 (ISO/IEC 19987:2024) natively for cross-platform portability.
No production-ready open-source stack exists that combines sensor ingestion, excursion management, and 21 CFR Part 11 / EU GDP compliance reporting in one place.

Key Features

Sensor Ingestion and Real-Time Monitoring

Real-time data ingestion via MQTT/HTTP from BLE, cellular, and LoRa sensors
Multi-sensor support for temperature, humidity, shock, light, and location in a unified event model
Configurable temperature and humidity alert thresholds
Email, SMS, and webhook notifications on excursions
Multi-temperature-range support (frozen, refrigerated, ambient-controlled)

Shipment Lifecycle and Chain of Custody

Shipment lifecycle tracking from created to in-transit to delivered
Chain-of-custody timestamp logging at transfer points
Historical excursion log with exportable PDF and CSV reports
Lane and carrier performance analytics dashboard

Compliance and Audit

21 CFR Part 11-compliant audit trail module with electronic signatures and tamper-evident logs
LLM-assisted compliance report generation for GDP/FDA excursion deviation reports
Multi-user role-based access (admin, quality, logistics, read-only)
EPCIS 2.0 (ISO/IEC 19987:2024) event export for supply chain interoperability

AI-Driven Analytics

ML-based excursion prediction trained on sensor, route, and ambient data
Lane and carrier risk scoring to prioritise quality audits
Alert noise reduction distinguishing genuine excursions from door-open events, defrost cycles, and sensor noise
Dynamic shelf-life estimation through cumulative thermal exposure modelling

Developer and Integration Surface

REST API with OpenAPI 3.1 specification for third-party integration
Webhook support for event-driven integrations
Open standard protocols (MQTT, AMQP, CoAP) for sensor communication
Hardware-agnostic design avoiding vendor lock-in

AI-Native Advantage

AI capabilities reposition cold chain monitoring from reactive logging to predictive operations. ML models on historical sensor, weather, and route data can forecast temperature breaches hours before they occur, enabling pre-emptive rerouting rather than reactive disposal. LLMs can auto-draft FDA 21 CFR Part 11 and GDP-compliant deviation investigation reports, eliminating manual write-ups. Continuous AI risk scoring across route, ambient conditions, carrier history, and product sensitivity focuses operator attention where it matters, while ML classifiers cut alert fatigue by separating true excursions from defrost cycles and brief door-open events.

Tech Stack & Deployment

The platform targets standard IoT protocols (MQTT, AMQP, CoAP) for sensor ingestion and GS1 EPCIS 2.0 (ISO/IEC 19987:2024) for cross-vendor data portability. A REST API documented with OpenAPI 3.1 and webhook delivery cover third-party and ERP/QMS/TMS integration. The data model is designed to accommodate BLE, cellular, and LoRa sensors without hardware lock-in, supporting both stationary (warehouse) and in-transit shipment scenarios.

Market Context

The global cold chain monitoring market was valued at approximately USD 8.3–23 billion in 2025, with Markets and Markets projecting USD 15.04 billion by 2030 (CAGR 12.6%) and GlobeNewsWire projecting growth to USD 81.77 billion by 2031 (CAGR 23.5%). Hardware loggers run ~$20–100/unit disposable, reusable trackers $3–8/device/day, and platform SaaS from $200–2,000+/month for small operators up to six-figure enterprise contracts. Primary buyers are pharmaceutical manufacturers and 3PLs (GDP/FDA), food processors and grocery chains (FSMA/HACCP), vaccine distributors (WHO guidelines), clinical trial logistics, and cold-storage warehouse operators.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.