Description
Module/Solution Overview
The City4Age inter-activity behaviour modelling algorithm has been designed to model the users’ behaviour following a stochastic approach and to be able to detect unusual patterns in the users’ everyday actions. It works over the actions that have been captured by the IoT infrastructure in the pilot sites and stored in the City4Age shared repository.
Innovation
The City4Age inter-activity behaviour modelling algorithm allows modelling and monitoring the behaviour of users, based on their daily life activities, in order to detect behaviour variations that could indicate a risk related to MCI or Frailty. This design is the result of analysing the needs of the five different pilots that take part in the project, each one with a different set of requirements. It was also designed taking into account the geriatricians’ needs.
Business Impact
Organisations that need to detect unusual behaviour can easily use the City4Age inter-activity behaviour modelling algorithm.
Interoperability
The algorithm can be easily integrated with any application that provides action or activity sequences.
Stakeholders profile
Health and wellness related apps that need to evaluate the user behaviour and detect unusual occurrences.
Competitors
Activity monitoring applications provide more naïve approaches to behaviour modelling. The City4Age inter-activity behaviour modelling algorithm offers a health and wellness oriented solution.
Future availability
Open Source
Contact info
Details
| Categories: | Models and Algorithms |
UDeusto
Universidad de la Iglesia de Deusto
The University of Deusto, recently recognized as an International Excellence Campus, was founded in 1886 and comprises 6 Faculties: Psychology and Education, Human and Social Sciences, Engineering, Law, Business and Economic Sciences and Theology. The Deutotech - MORElab (http://www.morelab.deusto.es/) research group is one of the largest and most successful research groups in the University and belongs to the Internet unit within DeustoTech – Deusto Institute of Technology, affiliated to the Faculty of Engineering of the University of Deusto. The group has a strong background in the application of Artificial Intelligence techniques to middleware for embedded and mobile system in order to foster context-aware reactivity and activity modelling and reaction. In addition, the group is currently focusing its research on the area of Smart Cities by leveraging its expertise on Ubiquitous Computing, Linked Open Data management and recommendation and social data mining (Big Data Analytics) to extract structured data from social networks and thus enable urban apps and services assisting the daily activities of citizens or visitors.
