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Autonomous distributed telemetry and edge intelligence operating layer
An open-source embedded edge telemetry and inference framework for microcontrollers and single-board computers, powering real-time industrial sensory diagnostics without cloud round-trips.
Industrial sensor clusters generate vast streams of high-frequency vibrational, thermal, and electrical telemetry that saturate uplink bandwidth and incur cloud latency. Krypton Edge runs quantized neural inference locally on ESP32-S3 and edge nodes, alerting on anomalies in sub-millisecond windows.
Microcontrollers execute an optimized FreeRTOS firmware in C++ that samples analog transducers at 10kHz. Quantized PyTorch weights are mapped into memory-mapped flash. Anomalous vectors are securely dispatched over WebSockets to local monitoring dashboards.
This project is actively welcoming builders. If your skill set matches the requirements below, reach out directly:
@elenavance
Designing ultra-low-power edge computing nodes, microkernel telemetry firmware, and on-device neural network inferencing pipelines on bare silicon.
