Real-Time Analytics at the Edge: Decisiones en milisegundos
Introducción
The rapid growth of IoT devices, industrial sensors, and autonomous systems has generated a new technological need: processing data in milliseconds near its source. Traditional cloud architectures, while scalable, introduce latencies incompatible with critical operations such as industrial control, predictive maintenance, and autonomous systems.
This white paper analyzes the architecture, implementation, and benefits of real-time data analytics in edge computing. The approach is based on three fundamental pillars:
- Distributed, event-driven processing architectures.
- Robust synchronization strategies between edge and cloud.
- Performance metrics specific to edge environments.
Based on real-world implementations in manufacturing, industrial IoT, and robotics, latency reductions of 80% to 95% have been observed compared to cloud-centric architectures. These improvements directly impact downtime reduction, bandwidth optimization, and increased operational availability.
Download this white paper to learn more about real-time data analytics!
