SWS Technologies

Edge Lab

Technical case studies on neuromorphic systems.

We explore the frontier of spiking neural networks, event-based sensing, and hardware-aware AI that thrives in constrained environments.

Case Study 01

SNN acceleration for event cameras

Designed an end-to-end inference pipeline for event-driven vision, including spike encoding, network compression, and latency profiling.

  • 15x latency reduction on edge targets
  • On-device calibration with adaptive thresholds
  • Streaming analytics for live telemetry

Case Study 02

Neuromorphic robotics control stack

Built a closed-loop control system leveraging spiking networks for adaptive motor control and resilience to noisy sensor input.

  • Sub-10ms feedback response
  • Adaptive learning on-device
  • Hardware-in-the-loop validation

Research Focus

Pulsar benchmarking and deployment playbooks

Comparative testing across neuromorphic targets with power profiling, throughput tuning, and deployment-ready reference architectures.

Data ingestion pipelines
SNN model tuning scripts
Edge deployment checklists