[u' @article{mulero_towards_2018, title = {Towards ambient assisted cities using linked data and data analysis}, issn = {1868-5137, 1868-5145}, url = {https://link.springer.com/article/10.1007/s12652-018-0916-y}, doi = {10.1007/s12652-018-0916-y}, abstract = {As citizens\u2019 age increases, smart cities must adapt to help them to age properly. The objective of the City4Age project is to create the future ambient assisted cities that will help the citizens to deal with mild cognitive impairments (MCI) and frailty. In this paper we present two of the tools developed during the project. The first one is a city-wide context-manager, which allows to store the citizens information using a semantic representation and share it following the linked open data paradigm. The second one are the individual care monitoring dashboards, which use the stored information to help the caregivers to analyze and interpret the citizens\u2019 behaviour, allowing to detect risks related to MCI and frailty.}, language = {en}, urldate = {2018-07-02}, journal = {Journal of Ambient Intelligence and Humanized Computing}, author = {Mulero, Rub\xe9n and Urosevic, Vladimir and Almeida, Aitor and Tatsiopoulos, Christos}, month = jun, year = {2018}, keywords = {AAL, AI for health, Ambient Assisted Living, Artificial Intelligence, City4Age, Data analysis, IF1.910, Linked Open Data, Q3, ambient assisted cities, machine learning, smart cities}, pages = {1--19}, } ']