Edge Computing
Edge Computing is the practice of processing and analysing data close to where it is generated — at or near the devices and sensors at the “edge” of the network — rather than sending all of it to a distant central cloud data centre. Computation happens on edge devices, gateways or local servers near the source.
The benefits are lower latency (faster response), reduced bandwidth and cost (less data shipped to the cloud), resilience (working even when connectivity is poor), and privacy. These matter greatly where connectivity is limited or real-time response is needed — a prime example being ships at sea, where satellite bandwidth is costly and intermittent, so processing sensor and machinery data on board (at the edge) and sending only summaries or alerts ashore is far more practical than streaming everything. In logistics, edge computing enables fast local decisions (an alarm on a reefer, an anomaly on machinery) and efficient use of scarce connectivity, working together with the cloud in a hybrid model. Edge computing is a key architecture for IoT-heavy, real-time and bandwidth-constrained environments like shipping, and complements central cloud analytics. It brings intelligence to where the data is.
Shipping data to a distant cloud is slow, costly and useless when the link drops — edge computing processes it right where it's created, giving fast local decisions and thrift with bandwidth. That is exactly what ships at sea need, with their scarce, pricey satellite links: process on board, send only what matters. It is a key architecture for real-time, connectivity-constrained IoT.
Why use edge computing instead of the cloud?
For lower latency, less bandwidth and cost, and resilience when connectivity is poor — processing data locally and sending only what is needed onward.
Why does edge computing suit ships?
Satellite bandwidth at sea is costly and intermittent, so processing sensor data on board and sending only summaries or alerts ashore is far more practical.