Welcome to ALONE project

The aging of population in recent years has become a key aspect in the definition of future social and health policies in Europe, a continent where people over 50 years old already constitute 37% of the population. Combined with an increased demand for long-term care in elderly, this evolution will constrain the sustainability of health systems. This challenge only seems achievable if the accessibility to care and suitable treatment is ensured, an aspect that becomes a critical issue in rural and semi-urban regions, where in Spain (and other European countries) the proportion of people over 65-year-olds or more is above the national average, and where there is often a less widespread access to social and health resources and services. To deal with this situation, European policies are increasingly focused on allowing older adults to live safely and independently at home, rather than institutionalizing them, through new strategies of care and treatment. In this context, the use of technological solutions for the home care digitization turns out to be an attractive and feasible solution in rural and semi-urban areas, where the people involved can be encouraged to live in their own environment for as long as possible, and with the best possible quality.

The main contribution of the project is the definition, design and development of a comprehensive system capable of using the power consumption from a home to non-intrusively monitor the daily activity of tenants, and use that information to digitize care at home, as well as to foster independent living of elderly, with a certain degree of dependency, and/or cognitive disorders, in rural areas with low population density. Based on a single, minimally invasive, electrical consumption measurement point, NILM techniques and intelligent systems will be applied to determine the electrical appliances active at any time. Not only high-power devices will be detected, but also those with lower consumption, whose detection is not solved in the current state of the art, and which are equally relevant for the subsequent identification of behavioural routines. From there, we will proceed: on the one hand, to the detection of anomalies in the short term; and, on the other hand, to the long-term monitoring of the performance of certain activities of daily life, as well as their evaluation, so that tools can be provided for the digitization of home care. The system will be based on an MPSoC architecture in an FPGA device that, locally (edge computing), will implement all the previously described algorithms in real time. Only the final results from the identification of household appliances and the recognition of activities will be sent to the cloud for further analysis. This minimizes the communication requirements of the local system, a key factor in rural areas with coverage restrictions.

Participants

GEINTRA group, University of Alcalá

• Dr. Álvaro Hernández
• Dr. José M. Villadangos
• Dr. María Carmen Pérez
• Dr. Jesús Ureña
• Dr. Daniel Pizarro
• Dr. Rubén Nieto (Rey Juan Carlos University)

Collaborators

• Dr. Antonio Ruano, University of Algarve, Portugal
• Laura de Diego, University of Alcalá

Contact:

Álvaro Hernández (University of Alcalá)