AI-Driven Cold Chain Monitoring and Predictive Logistics

In logistics and supply-chain operations where temperature-sensitive goods such as food, vaccines and pharmaceuticals must be handled with extreme care, OneData offers a comprehensive AI-Driven Cold Chain Monitoring & Predictive Logistics platform. This solution integrates IoT sensors, edge/cloud AI analytics, time-series modeling and predictive forecasting to ensure integrity of cold-chain shipments, optimise routing and proactively manage risk.

Real-Time Sensor Monitoring & Connectivity

OneData deploys IoT temperature and humidity sensors across transport units (refrigerated trucks, containers, and cold-storage units). Using AWS IoT Core, the sensors stream telemetry in real time to the cloud, where OneData’s platform monitors environmental conditions continuously and establishes baselines for acceptable range behaviour.

Anomaly Detection & Equipment Health Monitoring

Conditions outside the defined safe ranges trigger alerts. With AWS Lookout for Equipment, OneData applies AI/ML-based anomaly detection to sensor and equipment telemetry. It identifies early indicators of refrigeration unit failure, power-loss, door-open events, or gradual drift in temperature/humidity performance before they cause spoilage.

Predictive Logistics & Forecasting

***Using AWS Forecast, OneData’s solution ingests historical data on transport routes, temperature/humidity trends, logistics cadence, and equipment performance to build predictive models of delivery timing, risk of spoilage, and logistics bottlenecks. ***The platform provides recommendations for optimal routing, scheduling, and contingency plans (e.g., rerouting, pre-cooling, buffer inventory) to maintain cold-chain integrity.

Alerts, Dashboards & Visualisation

Through interactive dashboards (leveraging AWS QuickSight or similar visualization layers), logistics managers see current shipment status, key metrics (time-outside-range, cumulative deviation, equipment alerts), and predicted risk scores. Automated alerts (via email/SMS/app) are triggered when thresholds are breached or when forecast models predict impending risk so corrective action can be taken.

Use Cases

• Food Delivery & Perishable Shipping: Monitoring refrigerated trucks carrying produce, dairy, meat which ensures end-to-end temperature compliance, minimising spoilage, and optimising load scheduling.

• Pharmaceutical Logistics: Cold-chain tracking for vaccine shipments, biologics or temperature-sensitive drugs, ensuring regulatory compliance, maintaining temperature logs, and real-time alerts for deviations.

• Vaccine Supply Chain: Real-time oversight of storage and transport conditions for vaccines during last-mile delivery, contingency planning for route disruptions or equipment failure, and predictive modelling of risk zones.

Benefits

• Real-Time Quality Assurance: Continuous monitoring and immediate alerts ensure that deviation from safe environmental ranges is caught early.

• Automatic Alerts & Remediation: AI-driven detection of anomalies and automated escalation help reduce manual oversight and human error.

• Predictive Delivery Planning: Forecasting models help logistics planners anticipate delays, reroute shipments or proactively adjust schedules to maintain the cold chain.

• Reduced Spoilage & Losses: By detecting risk earlier and adapting logistics accordingly, wastage of perishable goods is significantly reduced.

• Regulatory & Compliance Readiness: Traceable records of temperature/humidity, alerts and corrective actions support compliance in regulated industries (food safety, pharma).

• Optimised Cost & Efficiency: Better scheduling, fewer losses, and proactive maintenance of refrigeration equipment contribute to lower operating costs and increased operational efficiency.