TY  - JOUR 
AU  - La Delfa, Gaetano C.
AU  - Prieto Tejedor, Javier
AU  - Monteleone, Salvatore
AU  - Rafique, Hamaad
AU  - Palesi, Maurizio
AU  - Patti, Davide
PY  - 2025
SN  - 2542-6605
UR  - http://hdl.handle.net/10366/167040
AB  - [EN]Indoor localization has gained significant attention in recent years due to its applications across sectors such as healthcare, logistics, manufacturing, and retail. However, while outdoor localization has been effectively addressed with GPS,...
LA  - eng
PB  - Elsevier B.V.
KW  - Indoor localization
KW  - Datasets
KW  - Machine learning
KW  - Smartphone sensors
KW  - Indoor positioning
KW  - Deep learning
KW  - Indoor navigation
TI  - Survey of smartphone-based datasets for indoor localization: A machine learning perspective
DO  - 10.1016/j.iot.2025.101753
T2  - Internet of Things
VL  - 34
M2  - 101753
ER  -