Incoming data prediction in smart home environment with HMM-based machine learning

Author(s):  
K. Zaouali ◽  
M. L. Ammari ◽  
R. Bouallegue ◽  
I. Sahloul ◽  
A. Chouaieb
2015 ◽  
Vol 9 (11) ◽  
pp. 55-62 ◽  
Author(s):  
M. Humayun Kabir ◽  
M. Robiul Hoque ◽  
Hyungyu Seo ◽  
Sung-Hyun Yang

Author(s):  
Andrej Zgank ◽  
Damjan Vlaj

The chapter presents acoustic presence detection, which can be applied to support the smart home system with information about the presence of humans in the environment. The acoustic presence detection is based on digital signal processing and machine learning methods, with the objective to classify the captured audio signal into the corresponding class. An analysis of different audio capturing devices for a smart home environment from the perspective of acoustic presence detection will be carried out. The presence detection task consists of voice activity detection, feature extraction, and classification. The extension of acoustic presence detection with additional information about the user's characteristics is proposed. This information can be used to optimize the smart home human-computer interface with personalization and customization functionalities.


2019 ◽  
Vol 36 (1) ◽  
pp. 203-224 ◽  
Author(s):  
Mario A. Paredes‐Valverde ◽  
Giner Alor‐Hernández ◽  
Jorge L. García‐Alcaráz ◽  
María del Pilar Salas‐Zárate ◽  
Luis O. Colombo‐Mendoza ◽  
...  

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