Edge Deployment of Crop Models on Low-Cost Microcontrollers

Rudi Hartono Universitas Diponegoro
Diterbitkan: 2025-12-15 Vol 1 No 2 (2025): Machine Learning for Agriculture Research Articles

Abstrak

A quantized model runs inference in 40ms on an ESP32, enabling in-field crop advisories without cloud connectivity across rural Indonesian farms.

Kata Kunci

  • edge computing
  • TinyML
  • agriculture
  • IoT

Referensi

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