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MY-AIR Project: Study on Semantic Location and Activity Recognition Algorithms for iOS Systems

Giovanni Clemente Monna

MY-AIR Project: Study on Semantic Location and Activity Recognition Algorithms for iOS Systems.

Rel. Giovanni Malnati, Elena Maria Baralis. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018

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Abstract:

SLAR (Semantic Location and Activity Recognition) algorithms studied on iOS systems. This thesis provides an algorithm for concurrent detection of semantic location and activity of the user, within a range of nine different possibilities. They are the combination of two possible semantic location states ("indoor" and "outdoor") and five different human activities ("stationary", "walking", "running", "biking" and "automotive"). The final output values are {automotive, indoor stationary, indoor walking, indoor running, indoor biking, outdoor stationary, outdoor walking, outdoor running, outdoor biking}. The recognition of these nine possible states is based on data coming from different smartphone sensors, selected between the less consumptive ones and basing on previous research works, for the applicationto be feasible and implementable. This branch of the research has been conducted on iOS systems, trying to overcome the limitations that this operative system presents if compared to the Android one. Then these SLAR algorithms will be used in a bigger project for recognizing the daily pollutant intake level of the user.

Relators: Giovanni Malnati, Elena Maria Baralis
Academic year: 2017/18
Publication type: Electronic
Number of Pages: 110
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Ente in cotutela: UNIVERSITY OF ILLINOIS AT CHICAGO (STATI UNITI D'AMERICA)
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/8027
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