Thanks to a new system developed at EPFL, building owners can detect the number of occupants and track their movement using sensors installed on floor slabs. This novel approach could be particularly useful for enhancing safety in retirement homes or managing buildings’ energy use more efficiently.

His method uses advanced algorithms – or more specifically, support vector machines – to classify the signals recorded by the sensors. Some interpretation strategies were inspired by the convolutional neural networks often employed in pixel-based image recognition, and can identify the footstep characteristics of specific occupants.

Real-world testing

The research team carried out four full-scale floor slabs: one in a seminar room at IMAC, one in an office environment at IMAC, one in the entrance of the MED building at EPFL campus and one in an open-hall space in Singapore. “These four case studies allowed us to validate our occupant detection, localization and tracking system on a larger scale. Unlike existing methods, ours needs fewer sensors – just one for every 15–75 m², as opposed to one for every 2 m² – and doesn’t require that the floor slabs have uniform rigidity. What’s more, the localization feature of other methods had been tested only on single individuals,” says Drira.

The new system has applications in a host of fields. It could be used to enhance energy management protocols in offices, improve building security (like at banks and data centers), find occupants during an emergency and locate patients inside hospitals and retirement homes. This system can do all that without infringing on occupants’ privacy.