This study presents the design and implementation of an Internet of Things (IoT)-based monitoring system for indoor temperature and humidity using an ESP32 microcontroller and a DHT11 sensor, aimed at preventing wall mold growth in humid environments. The system continuously collects environmental data, transmits it to a Firebase Realtime Database, and visualizes it through a web-based dashboard accessible via desktop or mobile devices. The research was conducted through stages of hardware assembly, software programming, and real-time testing under varying indoor conditions. Experimental results showed that the DHT11 sensor recorded temperature errors ranging from −0.5°C to +0.8°C (1.21%–2.67%) and humidity errors between −2% and +3% RH (2.86%–7.50%), both within acceptable tolerance limits for environmental monitoring. The dashboard effectively displayed temperature and humidity trends, with clear visual cues indicating mold-risk conditions when humidity exceeded 70%. The system achieved a 98% data transmission success rate and operated reliably over continuous 24-hour testing. These findings confirm that the integration of DHT11, ESP32, and Firebase provides a low-cost, stable, and accurate platform for continuous environmental monitoring. The web dashboard enhances user engagement through intuitive visualization and real-time feedback. Future improvements are recommended, including higher-accuracy sensors, automatic notifications, and adaptive control mechanisms for ventilation or dehumidification. Overall, the system demonstrates that IoT-based monitoring can serve as an effective early warning tool for indoor mold prevention and environmental quality management in tropical climates.