The goal of the AEOLUS project is to become the first to provide a field-tested holistic air quality solution. Currently, air pollution is measured regularly at selected locations, mainly at the largest sources of pollution and in city centres. Accurate air quality monitors are costly and bulky; hence the number of air pollution stations is limited.

The AEOLUS multi-gas sensor will target gases with fundamental importance for environmental sensing regarding air quality and toxicity in cases of gas leakage. By such means, the project consortium combines a series of technologies, among others are:

• MID-IR well-proven Absorption Spectroscopy sensing techniques, nondispersive infrared (NDIR) gas sensing approach;
• the high degree of on-chip integration along with wafer-scale manufacturing;
• low-cost and mass fabrication approach in terms of electronics and packaging;
• sensor system deployment into IoT testbed;
• Deep Learning algorithms, fed by a plethora of data;

The AEOLUS vision is to make the field-tested holistic air quality solution affordable, cloud-connected and ‘smart’ as well as facilitate and encourage citizen engagement and its widespread deployment into our communities, to meet the needs of Smart City applications and ultimately pave the way to affect necessary changes in our lives.

The quality of the air we breathe is a vital asset affecting human health and well-being, as well as environmental resources such as water, soil and forests. As the need to reliably monitor gas emissions is becoming more and more urgent in view of environmental challenges, the demand for ‘smart’, networked and truly affordable gas sensors will only grow.

AEOLUS aims to be the first to provide a field-tested holistic air quality solution. AEOLUS multi-gas sensor will target gases with prominent importance for environmental sensing regarding air quality and for toxicity in cases of gas leakage.

Key Objectives:

• Αffordable photonic gas sensing
• Portable photonic sensing system
• Cloud connectivity
• AI driven decisions
• Large scale adoption

Key Technologies:

• MID-IR well-proven Absorption Spectroscopy sensing techniques, nondispersive infrared (NDIR) gas sensing approach
• high degree of on-chip integration along with wafer-scale manufacturing
• low-cost and mass fabrication approach in terms of electronics and packaging
• sensor system deployment into IoT testbed

Deep Learning algorithms, fed by plethora of data