Air quality is invisible and strongly affects our health and performance. Also, air quality in cities changes dramatically from one hour to the next and from one block to another. A dense mesh of mobile miniaturized sensors reporting air quality, in real time, will help us to make informed decisions and in the long run to improve air quality.

Distributed and networked gas sensing is rapidly growing in importance for industrial, safety, and environmental monitoring applications. Optical gas sensors offer the highest sensitivity, stability and specificity in the market, but for most applications, the existing sensors are too bulky and expensive. To enable the broad utilization of high-performance gas sensor networks, there is a critical need for small, low-power and networked gas sensor systems.
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Why do we want air sensors everywhere and accessible to everyone?

Discover the story behind ULISSES.

In ULISSES, we will develop an integrated optical gas sensor and the networking technology required to bring it onto the Internet of Things (IoT). ULISSES will deliver the wafer-scale mass production methods necessary to enable production volumes of millions of sensors per year, and thus provide an order of magnitude reduction of sensor module cost.

By leveraging recent breakthroughs of the ULISSES partners on waveguide integrated 2D materials-based photodetectors, 1D nanowire mid-IR emitters, and mid‏-IR waveguide-based gas sensing, we target a three-order-of-magnitude reduction in sensor power consumption, thus permitting maintenance-free battery powered operation for the first time. Finally, we will implement a new edge-computed self-calibration algorithm that leverages node-to-node communications to eliminate the main cost driver of low-cost gas sensor fabrication and maintenance.
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New conference paper just released by KTH

The KTH team was represented by PhD student Gaehun Jo, at the International Conference on Wafer Bonding – WaferBond’22 held in October ...

Free-for-all workshop on "Integration of novel materials into silicon photonics"

The event, sponsored by ULISSES, is organised by AMO GmbH on November 21-22, 2022 in Aachen, bringing together experts from academia and ...

Publication in IEEE on Efficient time-adaptive Expectation Maximization algorithm for HMM tracking

Congrats to the KTH team for their publication in IEEE Transactions on Industrial Informatics "Time-Adaptive Expectation ...
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Hans Martin
Project coordinator
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82471 Delsbo
Kirsten Leufgen
Project manager
Rue du Centre 70
CH-1025 St-Sulpice
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825272 (ULISSES).