Towards interactive leaning for occupancy estimation
Document Type
Conference Article
Publication Title
Proceedings of the 2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016
Abstract
A new kind of supervised learning approach is proposed to estimate the number of occupants in a room. It introduces the concept of interactive learning where actual occupancy is interactively requested to occupants when it is the most valuable to limit the number of interactions. Occupancy estimation algorithms rely on machine learning: they use information collected from occupants together with common sensors measuring motion detection, power consumption or CO2 concentration for instance. Two different classifiers are considered for occupancy estimation with interactions: a decision tree C4.5 classifier and parameterized rule based classifier. In this paper, the question of when asking to occupants is investigated. This approach avoids the usage of a camera the determine the actual occupancy.
First Page
127
Last Page
133
Publication Date
1-1-2016
Recommended Citation
Amayri, Manar; Ploix, Stéphane; Reignier, Patrick; and Bandyopadhyay, Sanghamitra, "Towards interactive leaning for occupancy estimation" (2016). Conference Articles. 809.
https://digitalcommons.isical.ac.in/conf-articles/809
