AEOLUS, leveraging on the experience of its partners on novel photonic components (e.g. broadband thermal emitter, graphene photodetector), will demonstrate in an operational environment (TRL 7) an affordable, miniaturised, multi-gas (10 - 15 gases) sensor based on highly integrated photonic chips in the mid-IR (3 μm - 10 μm). AEOLUS sensors will be cloud connected, deployed in an existing IoT testbed, while the plethora of data acquired will be used to develop deep learning algorithms for chemometric analysis.
AEOLUS sensing system will demonstrate the calculation and accurate prediction of indoor and outdoor air quality, greenhouse gases concentration, and toxic gas leakages detection. The sensing system will provide many functionalities for the end-user such as real-time alerts, notifications, visualized reports and overlays while it will allow taking automatic actions where they are needed. AEOLUS will also demonstrate how user engagement can be promoted through its system, employing gamification concepts and incentivise the end users.
AEOLUS targets for a cheap portable sensor, tested for its interoperability, with many functionalities and quality of life services, targeting a very wide range of applications to ensure its widespread deployment. The proliferation of the AEOLUS sensor in the community acts in an exponential manner (leveraging Big Data techniques and Deep Learning algorithms), further enhancing the system’s accuracy and speed. AEOLUS sensing system is completely in line with its industrial partners' roadmaps and exploitation plans and it is foreseen to have a product in the market 0-2 years from the end of the project.
Ultimately, the acquired data and analysis will be made available to policy-makers and stakeholders, so that AEOLUS has a far-reaching impact in EU’s citizens life.
Field of science
- /natural sciences/computer and information sciences/data science/big data
- /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/sensors
- /engineering and technology/environmental engineering/air pollution engineering
- /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning
Call for proposal
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Funding SchemeIA - Innovation action
820 60 Delsbo