Design and implementation of a smart grain storage monitoring system

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Grain post-harvest losses due to deterioration during storage remains a prevalent challenge. The changes in environmental conditions if not monitored, can cause fluctuations in grain storage bins' temperature and humidity, leading to decay and infestation. Even though automatic grain monitoring systems have been developed they are not affordable. This project seeks to design an efficient and low-cost smart grain monitoring system to reduce unnecessary grain losses. To monitor grain conditions, the system employs temperature, humidity, and carbon dioxide sensors. Furthermore, this system employs machine learning classification algorithms to predict grain quality status (good or bad) based on sensor readings. The project implements the system prototype with 2 sensor nodes that communicate to a gateway through HC-12 transceiver modules.
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2022
post-harvest losses, grain storage