An Edge-Embedded Microcontroller Architecture for Grain Moisture State Estimation and Adaptive Drying Process Regulation

Abstract

Grain drying is a crucial post-harvest operation that significantly affects storage life, quality, and market value of agricultural produce. Traditional drying methods, mainly based on open sun exposure, are highly dependent on climatic conditions and require extensive manual effort, often resulting in uneven drying, contamination, and increased post-harvest losses. These limitations create the need for a more controlled, efficient, and reliable drying system. To address this issue, the proposed work presents an automated temperature-controlled harvester developed using the Raspberry Pi Pico microcontroller (RP2040-based microcontroller board). The system incorporates environmental monitoring through temperature and humidity sensors to continuously observe internal conditions within the drying chamber. Based on real-time data, the controller regulates heating and airflow mechanisms to maintain optimal drying parameters, ensuring uniform moisture removal and preventing over-drying or underdrying. The integration of a fan system and controlled heating element enhances air circulation and thermal distribution, improving drying efficiency. Additionally, the system includes a user-friendly interface that allows farmers to customize drying settings according to crop requirements. Emphasis is also placed on energy-efficient operation to reduce power consumption while maintaining performance. The proposed system offers a cost-effective, scalable, and sustainable alternative to conventional methods, improving grain quality, minimizing losses, and increasing overall agricultural efficiency. This intelligent approach supports the advancement of modern farming practices through automation and precise environmental control.