Summary of our expertise

• Indoor positioning using all existing infrastructure, like Wi-Fi, Bluetooth or loudspeakers (ultrasound positionning...)
• Detection of unusual behaviors (spending to much time in the bathroom, not passing by the kitchen at lunch time...)
• Detection of dangers (falling down, stress and panic, not getting up at wake-up time...)

We are currently working on different AAL projects (see http://tam.unige.ch), where we've already acquired a solid expertise in the above mentioned points. While we have also experience as coordinator (http://tam.unige.ch/projects/smartheat.html), in this new call we position ourself has technology provider. We want to provide data related to the position and the behavior of the user to a higher-level service, which can then use it in order to offer the best answer to the elderly person or his caregivers. In some scenarios (ultrasounds technique) the end-users doesn't need to wear any device to be localized.

Expertise on indoor positioning

Our indoor localization work is centralized in a module called GPM (Global Positioning Module). GPM offers a unified way to get your position via different technologies, like GPS, Bluetooth, Wi-Fi fingerprints or ultrasounds. We work also with industrials partners able to create new chips, for instance we are currently creating an UWB chip (size of a coin) allowing a positionning with an accuracy of 20cm.

Expertise on detection of unusual behavior

By studying the moves of a user in its home, we can detect unusual behaviors. For instance a user spending too much time in some areas (bathroom, corridor...) or that doesn't pass by some "checkpoints" (kitchen at lunch time, toilets for a while...) can be suspicious. Technically it consists in defining areas in the home and binding to each of them a set of rules. A rule that isn't met indicates a unusual behavior which deserves to be communicated to a caregiver.

Expertise on detection of dangers

While the detection of unusual behavior is GIS-based and rarely an emergency situation, this "detection of dangers" topic consists in analyzing the sensors of the mobile phone in order to be warned of a possible emergency situation. This includes the "classical" falling down that can be detected with the accelerometer, but also some more advanced analysis to detect when the user has an unusual high activity, indicating perhaps a panicking or a stressful situation.

We can provide a full sub-consortium!

Thanks to our currently running AAL projects and therefore our numerous links with industrial partners, we can if needed provide a full academic-SME sub-consortium. In this case, we as university would fully concentrate on the research aspects while our industrial partner would focus his work on the use cases and the industrialization of the product.

Why to choose us?

• Good experience in AAL projects (as partner and coordinator)
• With a total budget of 4M, Switzerland is a safe partner
• Good business experience
• Used to work with high quality standards (IS0 9001)
• Dissemination experience (publication and media)
• We can provide a full sub-consortium