Safety and Security

Emergency and personal risk management

This service alarms relevant people/entities in case of accidents or detection of potential dangers. Detection of such situations is:

  • automatically detected by the intelligence of the system thanks to the massive distribution of sensors across the environment (and even by sensors worn by the user) and/or
  • triggered by a user by pressing a panic button.

When the alarm is received at the care attention centre then an audio or videoconference may be started by the care centre towards the user. The alarm can be also sent to relevant persons to the mobile device so they can give support to the user as well. Then, the relative can initiate a normal telephone call or start a videoconference with the user.

This service had been tested in pilot sites of Spain and Denmark.

Automatic Management of the Environment for Comfort and Security (AMECS)

The aim is to monitor the daily activity of the user in order to do two types of actions: comfort related actions and to improve the security of the house.

The system is analyzing the information coming from the context sources and it’s continuously trying to discover certain situations: user goes to sleep, user cooks, user leaves home… The Activity Monitor component and the Situation Reasoner will provide this information. When it detects a situation it analyzes if there is any action linked with it and executes it. Actions can vary from local actuations to mitigate the risk to send an alert to an external system that receives it and provides some help to the user back.

The innovation compared to the existing domotic systems is that PERSONA can detect more situations, more complex and more precise than current domotic systems.

This service had been tested in pilot sites of Italy and Denmark.

Long Term behaviour analyzer

Window of Long Term Behaviour Analyzer software application

The aim is to create models of behaviour of an assisted person in a certain period of time, with the objective to compare two or more periods and detect potential changes in the quality of life of the assisted person.

The system collects as much information as possible from any source of information (sensors installed across the house in strategic places, in-door localization, performed activities like cooking or going out...). This information is analyzed and processed together to create a model of the behaviour of the user for a certain period of time. Models can be compared to detect changes in the behaviour that could show the existence of diseases in initial phase.

This service had been tested in the pilot site of Spain.