Gateways & Edge
Gateways and edge devices sit between the sensor and the cloud, aggregating nearby data and processing it close to where it is captured. An edge gateway beside a pitch can collect several feeds, run analysis on the spot, and send only what is needed onward. This middle layer is where privacy, latency, and reliability are largely won or lost, because it determines how much data has to leave a venue and how quickly a result is available.
Gateways & Edge
What a gateway does
Aggregating nearby sensors
An edge gateway collects data from several nearby sensors or devices and handles it as a group before anything reaches the wider network. It can synchronize feeds, run analysis locally, and decide what to forward. By concentrating work near the source, it reduces both the volume of data that travels and the delay before a result is ready.
Why process at the edge
Privacy, latency, reliability
Processing data near where it is captured keeps it local, which protects privacy; computes results without a round trip, which cuts latency; and keeps working when the network is flaky, which improves reliability. For live analysis in a gym or on a field, these are the difference between a usable tool and one that stutters or stalls.
The budget at the edge
Constrained but capable
Edge hardware is more capable than a wearable but still far more constrained than the cloud. Models must be sized to fit its power and memory, which shapes what analysis can run locally. As dedicated inference chips improve, the boundary of what an edge device can handle keeps moving outward, expanding what can be delivered on site.
A tiered system
Between device and cloud
Most real systems split work across three tiers: light processing on the device, aggregation and heavier analysis at the edge gateway, and the most demanding computation in the cloud when a connection allows. Understanding where a system draws these lines clarifies its privacy posture, its responsiveness, and how it behaves when connectivity fails.