Design and implementation of an IoT-based automated system for monitoring and regulating temperature, humidity, lighting, and ventilation in swiftlet houses using DHT22 sensors, NodeMCU, and a Web-based interface

Abstract

Swiftlet farming, a niche yet economically significant industry, relies heavily on maintaining precise environmental conditions, including temperature, humidity, lighting, and ventilation, to optimize bird activity and nest production. Traditional management methods are labor-intensive, prone to inconsistencies, and often ineffective. This study aimed to design and implement an IoT-based automated system using DHT22 sensors, NodeMCU ESP8266 microcontroller, and a web-based interface to monitor and regulate these critical environmental parameters efficiently. The system was deployed in a controlled swiftlet house environment for 90 days, with continuous data acquisition, real-time monitoring, and automated control mechanisms triggered upon threshold violations. Statistical analyses, including One-way ANOVA, paired t-test, Chi-Square test, and Wilcoxon Signed-Rank test, were performed to evaluate the system's performance. The results showed that temperature and humidity were maintained within optimal ranges (27.4±1.2°C and 85.6±3.4%, respectively) with statistically significant regulation (p < 0.05). Lighting levels remained stable without significant deviations (p > 0.05), and system reliability was validated with 99.2% uptime and an average response time of 1.8 seconds (p > 0.05). Furthermore, a 18.7% increase in nest yield post-implementation was observed (p < 0.01). The system's web-based dashboard provided user-friendly remote monitoring and control, reducing labor dependency and operational inefficiencies. Despite its successes, challenges such as reliance on Wi-Fi connectivity and the need for technical literacy were identified. Practical recommendations include integrating solar-powered modules, AI-based predictive analytics, and mobile application interfaces to enhance scalability and resilience. This study demonstrates that IoT-based systems offer a robust, cost-effective, and scalable solution for precision management in swiftlet farming, paving the way for broader adoption in smart agriculture.