PublishAux
Difference between revisions of "Senception"
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| − | '''SENCEPTION''' | + | '''SENCEPTION''' is a micro-company developing a personal cloud platform for contextualization and inference of roaming habits via wireless networks. |
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We are building a wireless and mobile network contextualization and inference platform, PerSense (TM). Our solution aims to boost a new type of services: inference and prediction of individual routines in close trusted circles, instead of only providing information about current geo-positioning. | We are building a wireless and mobile network contextualization and inference platform, PerSense (TM). Our solution aims to boost a new type of services: inference and prediction of individual routines in close trusted circles, instead of only providing information about current geo-positioning. | ||
Revision as of 09:19, 12 June 2017
SENCEPTION is a micro-company developing a personal cloud platform for contextualization and inference of roaming habits via wireless networks. We are building a wireless and mobile network contextualization and inference platform, PerSense (TM). Our solution aims to boost a new type of services: inference and prediction of individual routines in close trusted circles, instead of only providing information about current geo-positioning.
Senception's products have as value-add non-intrusive behaviour tracking and inference of user preferences as well as of social roaming habits. Our solutions are software-based, and available in the most used operating systems. Senception incorporates a team with extensive experience in industrial research, being currently involved in international projects (e.g. H2020) as well as national demonstration pilots (e.g. with the city of Portimão in Algarve).
Being a strong believer in research and innovation, Senception offers to research partners the possibility of exploiting light versions of its products.
Role in UMOBILE project
In UMOBILE, SENCEPTION leads Work Package 4, Services and Quality of Service. Senception is also the leader of task 4.2, focused on contextualization derived from network mining.