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Artificially intelligent ecosystem for self-management and sustainable quality of life in AAL

Reference number
Coordinator Mälardalens högskola - Akademin för innovation,design och Teknik, Eskilstuna
Funding from Vinnova SEK 4 146 148
Project duration June 2015 - November 2018
Status Completed

Purpose and goal

CAMI, a “Companion with Autonomously Mobile Interface” in an artificially intelligent ecosystem for self-management and sustainable quality of life in Ambient Assisted Living aims at creating a framework with an innovative architecture relying on Artificial Intelligence and allowing a seamless integration of any number of sensors and home appliances with commercial robotic platforms. CAMI’s final goal is to pave the road of “robots” into the field of ambient assisted living. CAMI is an integrated solution that offers services for social care, health care, home care and mobility.

Expected effects and result

CAMI project developed a modular and flexible system for integrating several technologies, platforms, and AI techniques. The CAMI system performs visualization of personal data based on remote monitoring, integrates biomedical sensors with the CAMI Gateway and CAMI cloud, robotic services for people detection and user interaction, fall detection, supervised exercises, home automation sensors control, etc. CAMI´s expected effects are: decreased cost of healthcare through self-care and monitoring, and user-friendly technology especially for people with special needs.

Planned approach and implementation

The CAMI prototype includes several components: CAMI Gateway, CAMI LinkWatch, Multimodal User Interface (gesture, voice), Telepresence Unit, Robotic Platform, and the CAMI Cloud. The CAMI devices can be combined into a basic or an extended system to support six different services: monitoring of physiological parameters, fall detection, home monitoring, user-robot interaction through reminders and user localisation, activity tracking, and support for physical exercises. CAMI´s capability to provide different system configurations is one of its strongest points.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 8 January 2019

Reference number 2015-05624

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