Design and implementation of a smart grain storage monitoring system
Date
2022-05
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Abstract
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.
Description
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
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Capstone Project
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Keywords
post-harvest losses, grain storage