Coordinator:   CNRS

Technical Support: LIRMM


The number of aging dependant people is remarkably growing. It is estimated that in France it will be multiplied by 1.4 from 2010 to 2030 and will double during the period from 2010 to 2060. This means that the number of dependant people in France will reach 1.6 million in 2030 compared to 1.1 million in 2010. Studies have also revealed that the majority of aging dependant people tends to stick in their private homes. The number of aging dependant people living in their houses is estimated to increase by 21.4% in France between 2005 and 2020. Whereas it will increase by only 2.5% in nursing homes. This induces different risks for the dependant person living alone and increases the stress and anxiety of the family and caregivers. The objective of the this test bed is to deploy and experiment the solution proposed in this proposal and validate its capability to detect the possible risks that can experience the aging dependant person and to help the family and caregivers rapidly react in such situations. The idea is also to maximize the period of stay in private homes for elderly people with mild dependence and help them keep a normal life (daily activities, going out, walk, shopping), while they are monitored by family members or caregivers.

City services involved

The test bed will be conducted in the city of Montpellier in France and will be leaded by the CNRS LIRMM laboratory. It will be supported by the agglomeration of Montpellier and the Hospital University Centre (CHU) of Montpellier. Montpellier Agglomeration offers different home assistance services for ageing people through two organisms (CCAS and DDASS). Our system will support these actions by allowing a continuous supervision of these people and a fast intervention when needed. A part of the deployments will be performed in the CHU of Montpellier to evaluate the proposed solution in a different context. The Agglomeration and the CHU of Montpellier will help, through their actual involvement in ageing care, to recruit volunteering ageing dependant people who will participate in the deployment experiments.

Target elderly population

Our services would have a direct impact on senior citizen, most of them being over 80 years-old, living alone with decreased physical abilities and may be suffering from mild dementia. They are surrounded by their family, at least occasionally, and they may benefit from the help of caregivers coming regularly, for food, hygiene, cleaning or any other service.

Interventions planned


- Keep the resident independent in his residence as long as possible.

- Reassure the resident to continue having a normal life while assisted by the proposed solution

- Reassure the family about the situation of the elderly person through following his activities, notifications and reminders.

- Create a gateway from individual houses towards the Nursing Home, for a smooth transition.

- Help the family and health services to quickly intervene in case a risk is suspected.

- Track the evolution of the health and cognitive skills of the elder.

- Offer a better logistic for the caregivers.


- Send an alert to the carer (either professional or family member), using Smartphone, email and SMS.

- Provide statistics over significant daily habits of the resident, to monitor her cognitive capacities.

- Offer a "Smart-home in a box" when the family needs to go away temporarily.

- Tell the caregiver if the patient is already having visit, so that they can come at the best time.

- Follow the resident outside and send alerts when needed.

Quantitative objectives

20 people over 75 years old

Increase the age at which the elder can live independently

Decrease the time of action when an elder is in danger (whether he fell down, or is wandering outside)

Provide indicators of the ability of an elder to live independently, given the evolution of her daily habits

Decrease the stress and the drop-out of the caregivers through a better logistic

Decrease the anxiety of the family, and all the negative outcome this anxiety may bring

Unobtrusive personal data available

Most data come from our pervasive system, gathered by sensors embedded in the environment:

Movements in the House

Uses of the bed

Uses of electronic devices

GPS for the outside

We benefit as well from human gathered data to determine the profile and habits of the elders:

Feedbacks from the caregivers and family

Presence of the caregivers