LoRa-based IoT System for Particulate Matter (PM) Monitoring in San Jerónimo, Cusco, Peru.

Abstract

The district of San Jerónimo in Cusco, Peru, faces a critical environmental crisis due to emissions from artisanal brick kilns and the lack of continuous air quality monitoring systems. In this context, pollution from fine particulate matter (PM2.5 and PM10) poses a significant risk to public health and local cultural heritage. This paper presents the design, implementation, and validation of a low-cost IoT sensor network based on LoRa technology to measure PM2.5 and PM10 concentrations in areas influenced by these activities. The proposed architecture integrates autonomous solar-powered sensor nodes, a LoRa gateway, and a cloud platform deployed on Google Cloud, utilizing InfluxDB and Grafana for time-series storage and near real-time georeferenced data visualization. Field tests in a semi-urban environment evaluated radio frequency coverage, network performance, and energy autonomy, validating an effective coverage of up to 2.39 km, an average packet delivery ratio (PDR) of 76.3%, and operational autonomy between 14 and 30 hours. The results demonstrate the viability and scalability potential of the solution as a support tool for municipal environmental management and evidence-based decision-making.