Abstract
There is a threat of ever-increasing air pollution levels, which can cause serious potential health issues, including respiratory diseases and also cancer. When air pollution crosses thresholds or reaches extreme levels, it is almost impossible to see it with our own eyes. This makes it much more dangerous and rampant. There needs to be a way to inform people in a user-friendly and easy-to-understand way to help show them the number of pollutants in the air and the effects that it may cause on their health, especially children. Therefore, we aim to create a solution to visualize the data using the current air pollution values and create visual insights to show the concentrated areas of air pollutants to the users. Starting with data collection using IoT devices and sensors, we intend to build a comprehensive system and workflow from scratch, ending with visual insights on the front end. By educating the public on air pollution particulates using simple visual, textual, and graphical representations via an app for Android and iOS devices, we aim to combat the rampant growth in air pollution particles. We will also provide valuable insights using machine learning models used for the prediction and analysis, to the users such as NGOs and government organizations that are working toward the reduction of pollution levels, to help them see what particular areas to target their efforts on.
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Rane, R., Bhamare, M., Patankar, R., Bobde, S., Kulkarni, P.V., Raju, M. (2023). Clarity-Air Pollution Monitoring System. In: Kumar, S., Hiranwal, S., Purohit, S., Prasad, M. (eds) Proceedings of International Conference on Communication and Computational Technologies. ICCCT 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-3485-0_33
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DOI: https://doi.org/10.1007/978-981-99-3485-0_33
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