Portable IoT-Based System for GIS Mapping of Urban Noise: a Case Study in Downtown San Salvador

This paper presents the development and implementation of a Mobile Internet of Things (M-IoT) system for real-time monitoring and mapping of noise pollution in the context of smart cities, using GSM technology and noise level (dB SPL) sensors. The system consists of a portable M-IoT node that collects georeferenced noise level data in real time and transmits it to an online platform, where the data are stored and processed to create heat maps. As a case study, the system was tested in the old downtown of San Salvador, El Salvador’s capital, over five days, using pedestrian routes for data collection. The results revealed that the noise levels during the morning and afternoon remained within acceptable limits (<60 dB). However, in the afternoon, the noise levels increased significantly, reaching 70 to 90 dB in most of the studied area, with critical peaks of up to 110 dB in specific locations, such as the Libertad park and the main intersections. These findings indicate a correlation between high noise levels and areas with heavy vehicular traffic and pedestrian activity. This system provides a cost-effective and scalable solution for monitoring urban noise pollution, making it highly suitable for cities in developing countries. The ability to visualize real-time noise data via GIS-based heat maps offers valuable insights for local authorities, enabling informed decision-making for noise management.