Original scientific paper
https://doi.org/10.24138/jcomss.v13i2.374
An IoT-aware AAL System to Capture Behavioral Changes of Elderly People
Luca Mainetti
; Innovation Engineering Department, University of Salento, Via per Monteroni, 73100, Lecce, Italy
Luigi Patrono
orcid.org/0000-0002-8591-1190
; Innovation Engineering Department, University of Salento, Via per Monteroni, 73100, Lecce, Italy
Andrea Secco
; Innovation Engineering Department, University of Salento, Via per Monteroni, 73100, Lecce, Italy
Ilaria Sergi
; Innovation Engineering Department, University of Salento, Via per Monteroni, 73100, Lecce, Italy
Abstract
The ageing of population is a phenomenon that is affecting the majority of developed countries around the world and will soon affect developing economies too. In recent years, both industry and academia are focused on the development of several solutions aimed to guarantee a healthy and safe lifestyle to the elderly. In this context, the behavioral analysis of elderly people can help to prevent the occurrence of Mild Cognitive Impairment (MCI) and frailty problems. The innovative technologies enabling the Internet of Things (IoT) can be used in order to capture personal data for automatically recognizing changes in elderly people behavior in an unobtrusive, low-cost and low-power modality. This work aims to describe the ongoing activities within the City4Age project, funded by the Horizon 2020 Programme of the European Commission, mainly focused on the use of IoT technologies to develop an innovative AAL system able to capture personal data of elderly people in their home and city environments. The proposed architecture has been validated through a proof-of-concept focused mainly on localization issues, collection of ambient parameters, and user-environment interaction aspects.
Keywords
Behavior Analysis; Bluetooth Low Energy; Cloud; Internet of Things; MCI; Smart Environments
Hrčak ID:
182535
URI
Publication date:
1.6.2017.
Visits: 2.288 *