Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa
Air quality is a crucial determinant of public health, significantly impacting global populations. According to the World Health Organization, air pollution causes approximately 7 million premature deaths each year, with 99% of the global population exposed to air that fails to meet recommended qual...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10852319/ |
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| author | Alexander Hilario-Tacuri Alberth Tamo Marco Pinares-Mamani Walter Butron Romel Jimenez |
| author_facet | Alexander Hilario-Tacuri Alberth Tamo Marco Pinares-Mamani Walter Butron Romel Jimenez |
| author_sort | Alexander Hilario-Tacuri |
| collection | DOAJ |
| description | Air quality is a crucial determinant of public health, significantly impacting global populations. According to the World Health Organization, air pollution causes approximately 7 million premature deaths each year, with 99% of the global population exposed to air that fails to meet recommended quality standards. Poor air quality leads to severe health issues, including respiratory and cardiovascular diseases. Given these alarming statistic, it is imperative for governments, organizations, and communities to prioritize air quality management. Effective measurement strategies are the first step in reducing health risks associated with pollution. Thus, to address this public health challenge, this article introduces a novel dynamic multi-source dispersion model that accounts for variations in wind velocity and direction over time, recognizing that air pollution is influenced by rapidly changing environmental factors. Additionally, three optimization problems are presented to identify the optimal locations for sensor nodes. The first problem enhances pollution sensing capabilities, the second maximizes the population served, aiming to ensure that air quality information is accessible to as many residents as possible, and the third one prioritizes the needs of vulnerable groups. Finally, we present results from a case study conducted on the campus of the National University of San Agustín in Arequipa, Peru, demonstrating the practical application of our proposed methodology in real-world scenarios. |
| format | Article |
| id | doaj-art-cf287435f4e8483c9cbd634a97ed9d5b |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-cf287435f4e8483c9cbd634a97ed9d5b2025-02-11T00:01:27ZengIEEEIEEE Access2169-35362025-01-0113241242413610.1109/ACCESS.2025.353409710852319Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in ArequipaAlexander Hilario-Tacuri0https://orcid.org/0000-0002-6299-3592Alberth Tamo1https://orcid.org/0000-0003-4915-6439Marco Pinares-Mamani2https://orcid.org/0009-0003-2006-9697Walter Butron3Romel Jimenez4https://orcid.org/0000-0002-1295-1546Department of Electronic Engineering, Universidad Nacional de San Agustín de Arequipa, Arequipa, PeruDepartment of Electronic Engineering, Universidad Nacional de San Agustín de Arequipa, Arequipa, PeruDepartment of Electronic Engineering, Universidad Nacional de San Agustín de Arequipa, Arequipa, PeruDepartment of Electronic Engineering, Universidad Nacional de San Agustín de Arequipa, Arequipa, PeruDepartment of Electronic Engineering, Universidad Nacional de San Agustín de Arequipa, Arequipa, PeruAir quality is a crucial determinant of public health, significantly impacting global populations. According to the World Health Organization, air pollution causes approximately 7 million premature deaths each year, with 99% of the global population exposed to air that fails to meet recommended quality standards. Poor air quality leads to severe health issues, including respiratory and cardiovascular diseases. Given these alarming statistic, it is imperative for governments, organizations, and communities to prioritize air quality management. Effective measurement strategies are the first step in reducing health risks associated with pollution. Thus, to address this public health challenge, this article introduces a novel dynamic multi-source dispersion model that accounts for variations in wind velocity and direction over time, recognizing that air pollution is influenced by rapidly changing environmental factors. Additionally, three optimization problems are presented to identify the optimal locations for sensor nodes. The first problem enhances pollution sensing capabilities, the second maximizes the population served, aiming to ensure that air quality information is accessible to as many residents as possible, and the third one prioritizes the needs of vulnerable groups. Finally, we present results from a case study conducted on the campus of the National University of San Agustín in Arequipa, Peru, demonstrating the practical application of our proposed methodology in real-world scenarios.https://ieeexplore.ieee.org/document/10852319/Air quality monitoringdeploymentdynamic dispersion modeloptimizationsensor deploymentwireless sensor networks (WSN) |
| spellingShingle | Alexander Hilario-Tacuri Alberth Tamo Marco Pinares-Mamani Walter Butron Romel Jimenez Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa IEEE Access Air quality monitoring deployment dynamic dispersion model optimization sensor deployment wireless sensor networks (WSN) |
| title | Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa |
| title_full | Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa |
| title_fullStr | Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa |
| title_full_unstemmed | Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa |
| title_short | Optimal WSN Deployment to Measure Air Quality in Dynamic Multi-Source Dispersion Scenarios: A Case Study in Arequipa |
| title_sort | optimal wsn deployment to measure air quality in dynamic multi source dispersion scenarios a case study in arequipa |
| topic | Air quality monitoring deployment dynamic dispersion model optimization sensor deployment wireless sensor networks (WSN) |
| url | https://ieeexplore.ieee.org/document/10852319/ |
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