Resumen:
The article presents the process of placing sensors in a multi-sensorial network, dynamically incorporating a
large number of heterogeneous input sources able to provide accurate monitoring data related with space
occupancy, energy consumption, comfort levels and environmental quality.To evaluate this multi-sensorial
network on real life conditions and on the specific business domains addressed by the Project, this sensing
network will be based on heterogeneous sensors (light, motion, CO2, CO, temperature, relative humidity,
existing infrastructure on video-surveillance, depth/range image generators, energy consumption, etc.) in
order to provide an all-inclusive perspective of covered spaces. Thearticleispart of a global
projecttodevelopprivacy-preserving human detection and tracking toolkit, whith the implementation of
algorithms for calibration of multiple-depth sensors in the architectural sketch up of a building (BIM), and
the development of techniques for extraction of occupancy-related statistics in the spatio-temporal domain
of a building. It is an architectural prototype agile and scalable, integrated with the extended LS middleware,
quepermite the training and calibration as decision making toolkit for Facility Managers.
