<p>A proper monitoring of the indoor environment is essential to maintain comfort, health, and proper control of energy. Variation in parameters like temperature, humidity, particulate matters, and intensity of light exerts a critical influence on health factors and working of devices. To mitigate the limitations of existing single-parameter-based solutions, it is proposed in this paper to design a multi-parameter IoT-based monitoring system such as temperature, humidity, and air quality (PM_2.5) that can be maintained with the assistance of ESP32-WROOM. It relies on the MQTT communication protocol and Wi-Fi technology to provide low latency data transfer. It is also modularly scalable with the choice of LoRa nodes for distant data communication. Experiments confirmed data accuracy with a 2% error margin to standard references, with a 215–310 ms latency and 99.1% packet delivery rate, outperforming existing technology on accuracy and power consumption. Regression and error analyses endorsed the accuracy with R² &gt; 0.98 and RMSE &lt; 0.5. The proposed architecture provides a low-cost and energy-efficient platform with scalability for continuous monitoring of dynamic indoor environments. The modularity and real-time analytical capability of this architecture could be useful for smart buildings and industry applications. It can contribute to sustainable infrastructure because it is energy-efficient and provides data analytics for environmental control.</p>