Web Application for Monitoring Pollution Levels in Smart Cities
As the world’s population is becoming increasingly urban, the cities are under pressure to remain livable. In recent years, the air quality of the cities has become one of the major cause of concern around the world.[5] In order to keep up with the fast-paced urbanization and technological progress in smart cities, it is crucial to establish reliable systems for monitoring the environment. This study focuses on the creation and execution of a web-based tool that aims to track pollution levels in intelligent cities. By incorporating live data collection from a network of sensors placed strategically throughout the city, this application can measure and monitor a range of pollutants, including PM2.5, PM10, CO2, NO2, and O3. After gathering the data, we send it to a central cloud platform for processing and analysis. This paper addresses the critical need for environmental sustainability in rapidly urbanizing areas by exploring the development of a web application that monitors pollution levels in intelligent cities using the OutSystems low-code platform. Using OutSystems accelerates the development cycle, ensuring rapid iteration and deployment of new features. The application ensures timely intervention by equipping authorities and residents with alert mechanisms that notify them whenever pollution levels surpass safe thresholds. The work proposes mostly a cloud based air quality detection system that analyzes the data for providing atmospheric quality to the user in real time.[10]
Authors
- Steven Abrantes (ORCID: https://orcid.org/0000-0002-4738-3745)
- João F. Pinto (ORCID: https://orcid.org/0000-0001-6499-310X)
- Diogo C. F. Silva (ORCID: https://orcid.org/0000-0002-3131-3232)
- Carlos Quental (ORCID: https://orcid.org/0000-0002-8598-2511)
- José Varanda
Institutions
- Polytechnic Institute of Viseu (PT)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.07.109
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00