A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-02, Vol.22 (3), p.1272
• Main Authors: Gómez-Suárez, Jaime, Arroyo, Patricia, Alfonso, Raimundo, Suárez, José Ignacio, Pinilla-Gil, Eduardo, Lozano, Jesús
• Format: Article
• Language: English
• Subjects: Air flow; Air monitoring; Air Pollutants - analysis; Air pollution; Air Pollution - analysis; Air quality; Air supplies; air-quality monitoring; Algorithms; Bicycles; Bicycling; Chemical sensors; Communication; Cyclists; electrochemical gas sensor; Environmental conditions; Environmental Monitoring; Evaluation; Gases; Humidity; International organizations; low-cost sensors; Lung cancer; Measurement techniques; Mental illness; Neural networks; Nitrogen dioxide; Optical measuring instruments; optical particle counter; Outdoor air quality; Particulate Matter - analysis; Pollutants; sensor calibration; Sensors; Urban environments
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22031272

We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO and O and an optical particle-matter (PM) sensor for PM . and PM concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user's understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform.