Triad AS7265x Multi-Spectral Spectroscopy & Diagnostic Dashboard

Seeed Studio XIAO ESP32-S3 to AS7265x Triad Sensor Wiring Guide

Hardware I2C interconnect schematic, pin mapping, and production firmware setup.

Physical Pin-to-Pin Interconnection Default I2C Bus @ 400 kHz

  ┌────────────────────────────────────────┐                 ┌──────────────────────────────────────┐
  │      SEEED STUDIO XIAO ESP32-S3        │                 │  SPARKFUN TRIAD SPECTROSCOPY AS7265x │
  │    (Dual-Core 240MHz, 8MB PSRAM)       │                 │   (AS72651 NIR + AS72652 + AS72653)  │
  ├────────────────────────────────────────┤                 ├──────────────────────────────────────┤
  │  [3V3]   Power Output (3.3V)           │═════════════════│  [3V3]  VCC Main Power (3.3V Reg)    │
  │  [GND]   Common Ground                 │═════════════════│  [GND]  Common Ground                │
  │  [D4]    GPIO 5 (Default Wire SDA)     │═════════════════│  [SDA]  I2C Data (Pullup to 3.3V)    │
  │  [D5]    GPIO 6 (Default Wire SCL)     │═════════════════│  [SCL]  I2C Clock (Pullup to 3.3V)   │
  │  [D3]    GPIO 4 (Optional Data Ready)  │┄ ┄ ┄ ┄ ┄ ┄ ┄ ┄ ┄│  [INT]  Interrupt Output (Optional)  │
  └────────────────────────────────────────┘                 └──────────────────────────────────────┘

XIAO ESP32-S3 Hardware Specifications

• Processor: Espressif ESP32-S3 dual-core Xtensa LX7 @ 240 MHz
• Memory: 512 KB SRAM, 8 MB PSRAM, 8 MB Flash
• AI Acceleration: Vector instructions (ESP-NN) optimized for SVM/MLP
• Default I2C Pins: SDA = Pin D4 (GPIO 5), SCL = Pin D5 (GPIO 6)
• Form Factor: Ultra-miniature 21 × 17.5 mm footprint (ideal for printhead)

AS7265x Sensor Specifications & Optics

• Channels: 18 calibrated optical channels (410 nm to 940 nm)
• Active Illumination: Onboard 405nm UV, 5700K White, and 875nm NIR LEDs
• Optimal Measurement Distance: Exactly 20 mm above AS72651
• Optical Enclosure: Ø 24 mm × 25 mm cylindrical shroud, PVC tape lined
• Communication Protocol: I2C Slave @ address 0x49

2D t-SNE Manifold Clustering (Perplexity = 30, Iterations = 350)

High-dimensional (18D) projection showing cluster separation inside the enclosure vs. open-air scatter.

Target Sensor: AS72651 @ 20 mm

Machine Learning Classifier Performance (5-Fold Cross Validation)

Recognition accuracy comparison across 12 mm, 16 mm, and 20 mm measurement distances (Figure 6).

Classifier	Hyperparameters Tuned	Accuracy	Precision	Recall	F1-Score	ESP32-S3 Latency
SVM (RBF Kernel) ★ Best	C=10, γ=0.1, RBF	98.95%	98.95%	98.95%	98.94%	1.84 ms
kNN (k=5)	Manhattan (L1), Distance weights	97.20%	97.39%	97.20%	97.16%	6.10 ms
Logistic Regression	L1 penalty (Lasso), C=9.0, liblinear	93.12%	93.10%	93.12%	93.04%	0.62 ms
MLP Neural Net	[18-18-32-18-13], ReLU + Softmax, Adam	92.65%	93.30%	92.65%	92.69%	0.85 ms

Multi-Class Confusion Matrix (SVM @ 20 mm Measurement Distance)