Analysis Of An Automatic Iot- Based Chili Plant Watering System Using Fuzzy Logic And The Adaline Algorithm

Abstract

Chili plants are high-value horticultural commodities whose growth and productivity are strongly influenced by water availability. Inaccurate irrigation practices can reduce crop yield and lead to inefficient water usage. This study proposes an automatic chili plant watering system based on the Internet of Things (IoT) that integrates soil moisture sensors, the Adaptive Linear Neuron (ADALINE) algorithm for sensor data validation, and fuzzy logic for irrigation decision-making. The system is developed using a NodeMCU microcontroller and is equipped with a web-based interface for real-time monitoring. Experimental results show that the proposed system is capable of classifying soil moisture levels into appropriate irrigation categories and automatically activating the water pump according to actual field conditions. Repeated tests conducted at different times demonstrate consistent and stable system performance. Therefore, the proposed system effectively improves irrigation accuracy, enhances water-use efficiency, and facilitates remote monitoring of chili plant conditions.