Air pollution is a severe environmental and public health concern driven by rapid industrialization and urbanization. Traditional air monitoring systems rely on fixed stations and manual observation, leading to delayed responses to hazardous gas leaks. This paper proposes an AI-enabled, IoT-based autonomous air monitoring system implemented on a four-wheel robotic platform. Controlled by an Arduino microcontroller, the robot navigates environments autonomously while continuously monitoring air quality using CO₂ and temperature sensors. An artificial intelligence-based algorithm analyzes the sensor data to generate multi-level warnings (Warning-1 to Warning-3) based on pollution severity. At critical gas concentrations (Warning-4), the system autonomously activates a timer and stops the robot to prevent hazards. IoT technology is integrated to transmit real-time data to a cloud server, enabling remote monitoring and alert generation via mobile devices. Furthermore, the system incorporates an energy-harvesting dual-fan mechanism that captures waste heat and airflow to generate electrical energy, improving the system’s sustainability. The proposed solution eliminates manual intervention, enhances environmental safety in hazardous zones, and supports the development of smart city infrastructure.

The AI-Enabled IoT-Based Intelligent Air Monitoring Sys- tem successfully demonstrates the integration of robotics, IoT, AI-logic, and energy harvesting to create a robust environmental safety tool. By providing continuous, auto- mated monitoring, the system eliminates the need for hu- man operators to risk exposure in toxic zones. The multi- stage warning algorithm ensures early detection, while the autonomous halt protocol prevents accidents in crit- ically polluted areas. The addition of the dual-fan energy harvester significantly enhances the sustainability of the robotic platform. The system is highly scalable and ready for deployment in smart cities, chemical plants, mining sites, and industrial factories.

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