Development of a Unified IoT Platform for Assessing Meteorological and Air Quality Data in a Tropical Environment

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 9; p. 2729
• Main Authors: Kairuz-Cabrera, David, Hernandez-Rodriguez, Victor, Schalm, Olivier, Martinez, Alain, Laso, Pedro Merino, Alejo-Sánchez, Daniellys
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01-05-2024; MDPI
• Subjects: Air pollution; Air quality; Decision making; Developing countries; Electronics; Engineering Sciences; Grafana; internet of things; Medical policy; monitoring system; Node-RED; Outdoor air quality; Public health; Sensors; TTGO TBeam; internet of things; monitoring system; low-cost sensors; weather station; TTGO TBeam; Grafana; Node-RED; air quality
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24092729

In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This study addresses this challenge by introducing an affordable internet of things (IoT) monitoring system capable of tracking atmospheric pollutants and meteorological parameters. The IoT platform combines a Bresser 5-in-1 weather station with a previously developed air quality monitoring device equipped with Alphasense gas sensors. Utilizing MQTT, Node-RED, InfluxDB, and Grafana, a Raspberry Pi collects, processes, and visualizes the data it receives from the measuring device by LoRa. To validate system performance, a 15-day field campaign was conducted in Santa Clara, Cuba, using a Libelium Smart Environment Pro as a reference. The system, with a development cost several times lower than Libelium and measuring a greater number of variables, provided reliable data to address air quality issues and support health-related decision making, overcoming resource and budget constraints. The results showed that the IoT architecture has the capacity to process measurements in tropical conditions. The meteorological data provide deeper insights into events of poorer air quality.