Supply Chain Glossary

This supply chain glossary terms provides detailed explanations through our mini blogs. Continue reading to increase your vocabulary and gain insight into the supply chain visibility with these terms!

Edge Computing in Logistics

Last updated: November 25, 2025
Logistics Supply Chain
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Edge computing in logistics refers to processing data near the source of data generation, such as sensors, GPS devices, or scanners, rather than relying only on centralized cloud servers. This localized processing allows for faster decision-making, reduced latency, and real-time insights that are critical for supply chain operations. It’s especially useful in time-sensitive logistics environments like last-mile delivery, cold chain transport, and warehouse automation.

How Edge Computing Works in Logistics?

In a typical supply chain, devices like IoT sensors, RFID scanners, or vehicle telematics collect large volumes of data. With edge computing, this data is analyzed and acted upon locally, either at the device or through a nearby gateway, before being sent to the cloud. This reduces dependence on internet connectivity and shortens response time. For example, if a refrigerated truck detects a temperature drop, an edge system can alert the driver instantly, avoiding spoilage before cloud systems even respond.

Key Features of Edge Computing

Low Latency Data Processing
Processes data on-site or nearby, enabling faster reactions to real-time events like equipment failures, route deviations, or inventory changes.

Reduced Bandwidth Usage
By filtering and analyzing data locally, only essential information is sent to the cloud, saving bandwidth and reducing communication costs.

Offline Capabilities
Continues to operate and make decisions even with limited or no internet access, ensuring uninterrupted logistics operations.

Benefits of Edge Computing in Logistics

Real-Time Decision-Making
Empowers supply chain teams to react instantly to disruptions or anomalies, reducing downtime and improving service quality.

Enhanced Operational Efficiency
Speeds up processes like sorting, picking, and vehicle monitoring by minimizing delays in data transmission and analysis.

Improved Asset Protection
Allows for quicker responses to temperature breaches, theft attempts, or mechanical issues, safeguarding goods and infrastructure.

Conclusion

Edge computing is revolutionizing logistics by bringing intelligence closer to where it’s needed most. It reduces lag, increases autonomy, and improves the responsiveness of supply chain systems. For logistics companies aiming to stay agile and efficient, edge technology offers a powerful advantage in real-time decision-making.