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Title	Iot Cloud-Based Air Quality Monitoring System With Arduino
ID_Doc	33757
Authors	Rajendrakumar P.M.; Shwetha P.; Reddy P.; Tejasri T.; Piruthiviraj P.
Year	2025
Published	Proceedings of 3rd IEEE International Conference on Knowledge Engineering and Communication Systems, ICKECS 2025
DOI	http://dx.doi.org/10.1109/ICKECS65700.2025.11034794
Abstract	Monitoring air quality is essential for protecting the environment and public health since rising air pollution levels offer serious health hazards. The IoT-based air quality monitoring system described in this study uses cloud computing and Arduino to gather and analyze data in real-time. The system uses a collection of sensors, including particle matter sensors (like the PMS5003) and gas sensors (such as the MQ-135 for detecting gases including smoke, carbon dioxide, and ammonia), which are interfaced with an Arduino microcontroller. The gathered data is transmitted through Wi-Fi or GSM modules to a cloud platform, like Blynk or Blynk, allowing for remote air quality parameter monitoring and analysis. The technology gives customers real-time updates on pollution levels and enables continuous monitoring of air quality in a variety of locations. A web interface or mobile application can be used to retrieve the data, making it simple to visualize patterns in air quality and to take prompt action. Furthermore, if the air quality deteriorates beyond predetermined levels, the system can be configured to deliver notifications, encouraging prompt action to limit exposure to dangerous contaminants. By enabling people, communities, and authorities to conduct well-informed decisions based on real-time air quality data, this IoT-based solution provides a scalable and reasonably priced method for broad implementation, helping to create smarter, healthier cities. © 2025 IEEE.
Author Keywords	Air quality monitoring; Alerts; Arduino; Blynk; Cloud technology; Data visualization; Environmental monitoring; Gas sensors; GSM module; IoT (Internet of Things); MQ-135; Particulate matter sensors; PMS5003; Pollution levels; Real-time data; Remote monitoring; Sensors; Smart. cities; WiFi

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