DEVELOPMENT OF SMART HOME USING ESP32 AND ARDUINO UNO WITH MULTIPLE AIR MONITORING AND CONTROL MODULES

Abstract

Modern homes face increasing demand for automation systems that are both intelligent and reliable, especially during network disruptions and power outages. Existing smart home technologies often encounter single-point failures due to overreliance on Wi-Fi or central hubs. This research addresses these limitations by developing a hybrid smart home system that integrates mobile automation with manual controls, emergency response, and renewable power. The system aims to provide resilience, sustainability, and real-time automation through the use of low-cost microcontrollers and IoT-based solutions. The study followed the Experimental Prototyping Methodology. The system layout was designed through 2D and 3D models using SketchUp. ESP32 and Arduino Uno microcontrollers were programmed in C++ through the Arduino IDE. Remote monitoring and control were enabled using the Blynk mobile application. Sensors such as MQ gas sensors, flame sensors, reed switches, and laser modules were tested and integrated to support air quality, fire, and security automation. A solar power system was included to address power outages. User feedback was collected through purposive sampling and assessed using a 4-point Likert Scale with descriptive analysis. The ESP32 successfully connected to Wi-Fi, with Blynk response times averaging 1–3 seconds under ideal conditions. MQ sensors detected air contaminants and activated exhaust fans for ventilation. During fire tests, flame sensors triggered alarms and sprinkler systems, while the Arduino-controlled water pump provided fire suppression. Gas sensors activated fan systems to expel hazardous fumes. Security modules using lasers and reed switches monitored and reported door and window activities as well as intrusions. Manual switches ensured system functionality during Wi-Fi or application failures. Circuit tests confirmed proper component interaction, demonstrating reliable prototype performance. The developed system exhibited robust multifunctionality by enabling real-time control and incorporating backup mechanisms. The findings confirmed the feasibility of combining mobile and manual control with safety automation and renewable power. Although field testing remained limited, the study suggested the need for larger user bases and long-term monitoring in future research. The model provided practical insights into the expansion of smart home applications, particularly in areas with limited connectivity.