IoT Based Smart Greenhouse Monitoring System With Fuzzy Logic - Nur Ainin Sofiya, Abu Kasim (2023)
This thesis presents a smart greenhouse monitoring system based on fuzzy logic for effective control of temperature, irrigation, and lighting conditions. Traditional greenhouse monitoring practices often require manual intervention and monitoring of soil moisture, temperature, humidity, and light intensity, leading to challenges in maintaining optimal plant growth. To overcome these limitations, an automated monitoring system is developed using fuzzy logic principles. The proposed smart greenhouse monitoring system autonomously monitors the plant's growing conditions. It employs fuzzy logic algorithms to continuously assess and adjust environmental factors. For example, when the temperature exceeds predefined thresholds, the system activates the ventilation system to regulate and maintain the desired temperature range for optimal plant development. The system further addresses the issue of manual watering by monitoring soil moisture levels. When the soil moisture falls below a specified threshold, the system automatically activates the water pump, providing adequate irrigation to ensure optimal soil moisture for plant growth. Additionally, the system incorporates an intelligent lighting system to optimize light intensity. It continuously monitors the light levels within the greenhouse and activates supplementary grow lights when the intensity decreases below the desired range, thereby promoting consistent and adequate light exposure for plants, even during nighttime hours. By employing artificial intelligence techniques and fuzzy logic control, the smart greenhouse monitoring system provides an automated solution to optimize temperature, irrigation, and lighting conditions. Through its autonomous actuation of the water pump and ventilation system, the system reduces manual intervention and ensures that plants receive optimal growing conditions. The results of this study indicate improved plant growth, enhanced crop yield, and reduced labor efforts for greenhouse cultivation. In conclusion, this thesis contributes to the field of smart greenhouse technology by presenting a comprehensive monitoring system that utilizes fuzzy logic control. The system effectively monitors and regulates temperature, irrigation, and lighting conditions, alleviating the need for manual intervention, and enabling optimized plant growth. The findings highlight the efficacy of the proposed system in providing efficient and automated monitoring for greenhouse environments, fostering improved cultivation practices, and maximizing crop yields.