Articolo in rivista, 2018, ENG, 10.1504/IJSNET.2018.10013426

Detecting occupancy and social interaction via energy and environmental monitoring

Crivello A.; Mavilia F.; Barsocchi P.; Ferro E.; Palumbo F.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

The demand for human oriented services in indoor environment has received steady interest and it is represent a big challenge for increasing the human well-being. In this work, we present a system able to perform room occupancy detection and social interactions identification, using data coming from both energy consumption information and environmental data. We also study the application of supervised and unsupervised learning techniques to the reference scenario, in order to: i) infer context information related to socialisation aspects, by recognising in real-time social interactions; ii) identify when a room is really occupied by workers or not, for emergencies management. The system has been tested in a real workplace scenario, inside three rooms of the CNR research area in Pisa occupied by different numbers of workers, representing the main core technology for future active and assisted living services.

International journal of sensor networks (Online) 27 (1), pp. 61–69

Keywords

Occupancy detection, Social interactions, WSN, Wireless sensor network

CNR authors

Mavilia Fabio, Crivello Antonino, Ferro Erina, Barsocchi Paolo, Palumbo Filippo

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 387702

Year: 2018

Type: Articolo in rivista

Creation: 2018-06-05 11:02:57.000

Last update: 2021-12-17 17:23:04.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:387702

DOI: 10.1504/IJSNET.2018.10013426

ISI Web of Science (WOS): 000434138500006

Scopus: 2-s2.0-85048043215