Indirect Recognition of Predefined Human Activities

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ID: 110221
2020
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Abstract
The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants. KNX (Konnex) standard-based devices were selected for smart home automation and data collection. The obtained data from these devices (Humidity, CO2, temperature) were used in combination with two wearable gadgets to classify specific activities performed by the room occupant. The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning control. The obtained results yield accurate classification.
Reference Key
gorjani2020sensorsindirect Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ojan Majidzadeh Gorjani;Antonino Proto;Jan Vanus;Petr Bilik;Majidzadeh Gorjani, Ojan;Proto, Antonino;Vanus, Jan;Bilik, Petr;
Journal sensors
Year 2020
DOI
10.3390/s20174829
URL
https://doi.org/10.3390/s20174829
Keywords
Deep learning artificial neural network Logistic regression prediction classification smart homes activity recognition intelligent buildings

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