IoT-Integrated Machine Learning for Precision Watering in Bamboo Mushroom Farming

Abstract

This study offers a method for enhancing bamboo mushroom farming. We aim to increase productivity by combining machine learning methods for device-level computing with the Internet of Things (IoT). The first step is to record the ideal environmental conditions in the bamboo mushroom greenhouse. The IoT devices collect data on temperature, humidity, soil moisture, and water usage, storing it in the cloud. The regression model is then formulated for irrigation control and predicting water consumption in the bamboo mushroom farm. Later, the microcontroller is programmed to control the water pump in a systematic manner to release water. The study found that temperature, soil moisture, and relative humidity are the primary factors affecting water content. The proposed method increased mushroom volume by 46.67% and saved 22% of water usage, demonstrating the successful integration of machine learning into smart farming at the device level.