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Development of Air Quality Monitoring System Using IoT

  • Nidhi Gupta,
  • Shrey Vashist,
  • Vivek,
  • Diwash Manjhi

摘要

The Air Control Monitoring System (ACMS) represents a significant technological breakthrough in the field of environmental management, offering a real-time solution for monitoring various air quality parameters at indoor and outdoor. This summary elucidates the fundamental principles, functionalities, and importance of the ACMS within the context of contemporary environmental challenges. Through the integration of advanced sensor technologies, data processing algorithms, and communication infrastructure, the ACMS provides a comprehensive framework for tracking air pollutants. The growing concerns about detrimental effects of air pollution on diverse ecosystem underscore the pressing need for accurate air quality monitoring. The ACMS effectively addresses this need by delivering continuous and high-resolution data on an array of pollutants, including particulate matter and moisture. This data empowers regulatory authorities, policymakers, and local communities to make well-informed decisions to enhance air quality in public welfare. As the prominence of the ACMS grows, challenges like calibration, data precision, and sensor dependability need to be addressed. Each country sets health-based criteria and targets for specific air pollutants, making atmospheric content detection and measurement more crucial than ever. Planning measures carefully is crucial which can be done effectively on the basis of data collection. The location of monitoring stations is one of the key elements that affect how representative the data that are collected. Monitoring station planning and setup are time-consuming and expensive processes. To track the amounts of different contaminants in the air, an IoT-based real-time ACMS is projected for indoor and outdoor. The region is divided between park and residential zones. This article suggests a simple and effective Internet of Things (IoT) system that could be installed anywhere and store the observed data.