Technology Overview
KiSTI combines motorsport-grade sensors, a production ECU, and edge AI into a unified telemetry platform. Here's how data flows from sensor to insight.
System Architecture
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→Data Pipeline
1. Sensor Layer
13 high-frequency sensors (brake temps, tire temps, EGT, boost, oil temp/pressure, wideband O₂) sample at 4-10Hz via analog/CAN interfaces.
Brake FL/FR/RL/RR thermocouples, tire FL/FR/RL/RR infrared sensors, K-type EGT probe, MAP sensor, NTC thermistor, oil pressure sender, Bosch LSU 4.9 wideband.
2. Vision Layer
4 front-mounted cameras feed directly to the Jetson Orin via USB 3.0 and CSI — thermal, depth, visual, and weather sensing.
Teledyne FLIR thermal IR, 3D LiDAR point cloud, high-speed RGB camera, weather/ambient conditions camera.
3. ECU Aggregation
Link G4X ECU receives all sensor data via CAN bus, applies calibration tables, and streams merged telemetry over USB.
500Kbps CAN, 100+ channels available, configurable output rates, real-time fuel/ignition corrections.
4. Edge Inference
NVIDIA Jetson Orin processes telemetry and vision data at the edge — anomaly detection, pattern matching, and predictive diagnostics in <50ms.
40 TOPS AI performance, TensorRT optimized models, 4 camera inputs, local data buffering when offline.
5. Cloud Sync
Zeus Memory ingests telemetry via WiFi/cellular with store-and-forward. AI findings surface in real-time dashboards.
pgvector semantic search, 3.5M+ memories, automatic embedding via Voyage AI, Slack/email alerts.
17
Sensor Channels
4-10 Hz
Sample Rate
<50ms
Edge Latency
500 Kbps
CAN Speed
40 TOPS
AI Performance
3.5M+
Cloud Memories