Intelligent mushroom cultivation: A machinelearning-based monitoring and automation system
This study investigates an automatic mushroom cultivation monitoring system that employs machine learning to enhance oyster mushroom development; two microcontrollers were used in this study. A Raspberry Pi 4 Model B analyses visual and environmental data to identify growth phases and adjusts light...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
IEEE
2025
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/46161/1/Intelligent_Mushroom_Cultivation_A_Machine_Learning-Based_Monitoring_and_Automation_System.pdf http://10.1109/INECCE64959.2025.11151087 https://umpir.ump.edu.my/id/eprint/46161/ |
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| Summary: | This study investigates an automatic mushroom cultivation monitoring system that employs machine learning to enhance oyster mushroom development; two microcontrollers were used in this study. A Raspberry Pi 4 Model B analyses visual and environmental data to identify growth phases and adjusts light colour accordingly. Meanwhile, the ESP32 monitors the temperature, and humidity levels and activates fans or humidifiers as needed. This system is a real-time technology intended to eliminate the need for manual labour as well as to ensure consistent growing conditions, resulting in increased mushroom output, quality, and sustainability. The results show that it efficiently maintains adequate developmental conditions while reducing energy usage through targeted environmental control. By using low-power devices and automating cultivation, the system also minimizes resource wastage and operational costs, making it both eco-friendly and cost-effective. |
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