Edge AI Engineering Service

01

System Architecture & Feasibility Design

Why it matters

Getting compute, memory and latency right at the start prevents dead-ends later. We size MCU/MPU/NPU, memory maps, and safety/security hooks.

What we do

Block diagrams, timing budgets, sensor lists, platform picks (S32K3 / STM32H7 / i.MX93), feasibility of model execution and power targets.

Deliverable: Architecture deck + feasibility report Outcome: Clear go/no-go with BOM direction

02

Hardware Co-Design & AI-Optimized Board Development

Why it matters

Signal integrity and sensor bandwidth determine AI quality. The PCB is part of the model.

What we do

Sensor front-ends (IMU, ToF, current, camera), high-speed links (MIPI, CAN, Ethernet), power/thermal analysis; Altium/KiCad bring-up.

Deliverable: Schematics + layout + validation Example: Predictive-maintenance board with sync’d accel + temp

03

Firmware & Driver Development for Sensor Integration

Why it matters

Deterministic, timestamped data streams feed stable inference. Jitter kills real-time AI.

What we do

DMA/MDMA HAL drivers, ISR latency profiling, RTOS task graphs, ring buffers for ADC/SPI/CAN/Ethernet.

Deliverable: BSP/HAL + timing report Example: CAN + ADC sync for motor torque inference

04

Data Acquisition & Preprocessing Frameworks

Why it matters

Clean features = confident models. Preprocessing belongs close to the sensor.

What we do

Fixed-point DSP (FFT, RMS, kurtosis, MFCC), scaling/windowing, logging tools for dataset creation.

Deliverable: C/C++ feature modules + Python logger Example: 10 kHz vibro data for autoencoder training (STM32)

05

AI Model Conversion & Quantization

Why it matters

Cloud-trained models must fit KB-scale memory and still hit latency targets.

What we do

TF/ONNX → TFLM, CMSIS-NN, Glow, eIQ; INT8 quantization, pruning, op-fusion, arena planning.

Deliverable: Deployable C/C++ inference lib + metrics Example: 5 MB CNN → 220 KB (-1.2% acc drop)

06

Embedded AI Inference Pipeline Integration

Why it matters

Inference must play nicely with control loops and comms — no missed deadlines.

What we do

DMA → Preprocess → Model → Action loops; MCU+NPU co-execution (Ethos-U); output via CAN/MQTT/IO.

Deliverable: Integrated fw + latency/FPS/RAM report Example: 1 ms loop with anomaly inference (S32K3)

07

Algorithm Design & Feature Engineering

Why it matters

Efficient hybrids (DSP + ML) often beat heavy nets on MCUs with better explainability.

What we do

SVM/RandomForest + fixed-point features; 1D-CNN stacks; anomaly scoring; parameter-tune tools.

Deliverable: Algo spec + runtime C/C++ Example: Compressor fault classifier (FFT + 1D-CNN)

08

Multi-Sensor Fusion & Context Awareness

Why it matters

Fusion reduces false positives and adds robustness in real environments.

What we do

Time-sync via hardware timers; EKF/UKF/Particle filters; CNN-LSTM fusion heads; dropout/jitter tolerance.

Deliverable: Fusion libs + calibration tools Example: Camera+ToF depth assist on i.MX93 NPU

09

Edge Connectivity & Cloud Integration

Why it matters

Insights must reach enterprise systems securely and efficiently.

What we do

MQTT/HTTP/WebSocket/OPC-UA; CBOR/JSON schemas; delta uploads; OTA model delivery via AWS/Azure/GCP.

Deliverable: Device→Cloud SDK + sample dashboards Example: NILM edge analytics mirrored to AWS IoT

10

Security-Enhanced Edge AI Implementation

Why it matters

Models and data are IP. Protect boot chain, keys, and inference integrity.

What we do

Secure Boot & anti-rollback; HSM/SE (S32K3 HSE, ST CSEc, SE050); TLS 1.3; encrypted model blobs + MAC.

Deliverable: Threat model + provisioning scripts Example: AES-GCM model integrity on S32K3

11

Verification, Validation & HIL Testing

Why it matters

Determinism and reliability make AI product-grade, not just a demo.

What we do

Hardware-in-loop benches, signal replay, golden vectors, fault injection, soak tests with reports.

Deliverable: Validation pack + traceability Example: 100-hour endurance with zero missed deadlines

12

Performance, Power & Thermal Optimization

Why it matters

Edge devices run 24/7 — efficiency defines viability and cost.

What we do

SIMD/NEON rewrites, cache-aware tiling, DMA double-buffering, power/FPS trade-off profiling, thermal limits.

Deliverable: Before/after optimization report Example: 450 mW → 260 mW on STM32H7

13

Compliance, Safety & Certification Readiness

Why it matters

OEM adoption needs compliance evidence and repeatable processes.

What we do

Map artifacts to AIS-189/UN R155/ISO 21434, IEC 62443, DLMS/COSEM; documentation and audits support.

Deliverable: Compliance matrix + evidence pack Example: ISO 21434 dossier for ADAS prototype

14

MLOps & Lifecycle Management for Edge Fleets

Why it matters

Models drift. Update securely without recalls and measure impact.

What we do

Versioned model registry, A/B on device, telemetry KPIs, drift detection, secure OTA, rollback guardrails.

Deliverable: Model lifecycle playbook + tooling Example: Secure OTA for 5k meters with shadow tests

15

Training, Documentation & Knowledge Transfer

Why it matters

Long-term success means your team can sustain and scale independently.

What we do

SDKs, API refs, CI scripts, playbooks; hands-on workshops on NXP eIQ, STM32Cube.AI, Edge Impulse.

Deliverable: Full docs + recorded training Example: 2-day embedded AI bootcamp (AutoBoardV1)