Development of a web-based automation system utilizing DHT22, BH1750, MQ-135, and soil moisture sensors for climate and environmental control in vertical farming structures

Abstract

The increasing demand for sustainable and efficient agricultural practices has driven the adoption of vertical farming systems integrated with IoT-based automation technologies. This study aimed to develop and evaluate a web-based automation system utilizing DHT22 (temperature and humidity sensor), BH1750 (light intensity sensor), MQ-135 (air quality sensor), and soil moisture sensors for real-time environmental monitoring and control in vertical farming structures. The system was designed to autonomously manage temperature, humidity, light intensity, air quality, and soil moisture, using an ESP8266 microcontroller and a web-based interface for data acquisition and control. Data were collected over 60 days and analyzed using statistical tools such as paired t-test, one-way ANOVA, Pearson correlation, and chi-square tests. The results demonstrated significant improvements in environmental parameter stability, with 85% consistency in temperature and humidity control, optimized light intensity across layers, and effective CO₂ regulation. Soil moisture levels were maintained within optimal thresholds, leading to 25% higher crop yield and 15% reduced water consumption compared to manually controlled systems. The findings validate the effectiveness of IoT-based systems in enhancing vertical farming efficiency and productivity. Future research should focus on incorporating machine learning algorithms for predictive control and energy optimization to further refine system performance.