NanoSen-AQM - Development and field validation of a low-cost nano-sensor system for real-time monitoring of ambient air quality (PI: Bernardete Ribeiro; co-PI: Alberto Cardoso)

Description

NanoSen-AQM's challenge is to monitor ambient air pollution and inform air quality to the public in real time in a sustainable way. The goal is to develop an electronic system based on low cost and low consumption sensors and validate the system at different locations in the Sudoe territory, based on certified instruments for measuring air pollutants. The electronic system uses gas sensors based on nanotechnology and microelectronics, machine learning techniques to discriminate and quantify toxic gases in the air, and cloud computing technology for managing and visualizing air quality. Small in size, lightweight and easy to use, the system is easily integrable into stations, mobile units and personal air pollution measurement equipment and thus suitable for use in sensor networks. These provide high spatial and temporal resolution data, which allow the validation of predictive models of air quality. The main outputs are high-performance nanosensors for the detection of toxic gases in the air; multi-sensor systems adaptable to a wide variety of platforms for monitoring air quality; and a cloud computing system to monitor and predict air quality and inform and raise public awareness about air quality. The outputs benefit the companies that manufacture and / or sell air pollution measurement instrumentation and high value-added environmental services companies, which facilitate decision making to the competent entities in air quality management, emission control and protection of sectors affected by air pollution. They participate in the NanoSen-AQM proposal, universities, R & D centers, SMEs and public administrations in Spain, France and Portugal. The transnational nature of the partnership allows the value chain to be covered and addresses the cross-border nature of air pollution.

Researchers

Funded by

SOE2/P1/E0569 (EU-INTERREG-SUDOE)

Partners

CSIC - Consejo Superior de Investigaciones Cientifica, UEX, Aiguasol, Universidade de Évora, CNRS-CIRIMAP, LAAS-CNRS, IRAY, Diputación de Ávila, Junta de Extremadura, AMB Área Metropolitana de Barcelona, EEA-CODA Ecologistas en Acción, UPM-ETSI

Total budget

1 950 000,00 €

Local budget

210 200,00 €

Keywords

Deep Learning, Air Pollution, Adaptive multi-sensors

Start Date

2018-04-01

End Date

2021-03-31

Journal Articles

Conference Articles