[u' @inproceedings{mulero_aal_2017, address = {Split}, title = {An {AAL} system based on {IoT} {Technologies} and {Linked} {Open} {Data} for elderly monitoring in {Smart} {Cities}}, abstract = {The average age growing of the urban population, with an increasing number of 65+ citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly\u2019s environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper presents a city-wide general IoT-based sensing infrastructure and a data management layer providing some REST and Linked Open Data Application Programming Interfaces (APIs) that collect and present data related to elderly people. In particular, this architecure is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) disease.}, booktitle = {2nd {International} {Multidisciplinary} {Conference} on {Computer} and {Energy} {Science}}, author = {Mulero, Rub\xe9n and Almeida, Aitor and Azkune, Gorka and Mainetti, Luca and Mighali, Vincenzo and Patrono, Luigi and Rametta, Piercosimo and Sergi, Ilaria}, month = jul, year = {2017}, keywords = {AI for health, Ambient Assisted Living, Artificial Intelligence, City4Age, Internet of Things, IoT, Linked Open Data, intelligent environments, machine learning, semantic inference, smart cities, sparql}, } ']