Ron Martino describes edge computing in physical terms. Farms using most of the world’s fresh water while losing half of it to imprecise irrigation. Factories generating massive waste through inefficient processes. Vehicles and industrial systems that cannot wait for distant infrastructure to decide how to respond to risk.

In each case, the constraint is the same: too much data, too much latency, and too much consequence to rely on centralized processing alone.

What changes is where intelligence lives. Sensors and embedded systems assess conditions locally, act in real time, and share only what needs to travel upstream. That shift reduces energy consumption, improves safety, and allows critical systems to continue operating even when connectivity fails. Cloud computing remains essential, but its role evolves, working in concert with distributed intelligence rather than replacing it.

Key takeaways:

• Processing at the source reduces waste at scale: From irrigation to industrial output, localized intelligence enables resources to be applied with precision instead of excess.
• Edge and cloud operate as a coordinated system: Local environments handle immediacy and autonomy, while centralized systems aggregate insight and optimize performance over time.
• Operational resilience starts locally: Factories, vehicles, and infrastructure must continue functioning safely even when disconnected from centralized networks.
• Security must be embedded from the start: Device identity, secure provisioning, encrypted data handling, and lifecycle management form the trust foundation for connected environments.
• Sovereignty emerges through system design: Control over how data is processed, moved, and retained is exercised architecturally at the edge, not just through governance frameworks.