Spatial computing for ambient intelligence: sensing and services of load-sensing floors

Abstract : This thesis explores the capabilities of an ambient intelligence equipped with a load-sensing floor. It deals with the problem of perceiving the environment through a network of low-resolution sensors. Challenges include the interpretation of spread loads for objects with multiple points of support, weight ambiguities between objects, variation of persons’ weight during dynamic activities, etc. We introduce new techniques, partly inspired from the field of computer vision, for detecting, tracking and recognizing the entities located on the floor. We also introduce new modes of interaction between environments equipped with such floor sensors and robots evolving inside them. This enables non-intrusive interpretation of events happening inside environments with embedded ambient intelligence, with applications in assisted living, senile care, continuous health diagnosis, home security, and robotic navigation
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Theses
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http://docnum.univ-lorraine.fr/prive/DDOC_T_2015_0293_ANDRIES.pdf
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https://hal.univ-lorraine.fr/tel-01754587
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Submitted on : Friday, March 30, 2018 - 9:54:07 AM
Last modification on : Tuesday, April 24, 2018 - 1:33:17 PM

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  • HAL Id : tel-01754587, version 1

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Mihai Andries. Spatial computing for ambient intelligence: sensing and services of load-sensing floors. Other [cs.OH]. Université de Lorraine, 2015. English. ⟨NNT : 2015LORR0293⟩. ⟨tel-01754587⟩

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