Title :
Multisensor data fusion model for activity detection
Author :
Wichit, Nattawut
Author_Institution :
Dept. of Comput. Eng., Prince of Songkla Univ., Songkhla, Thailand
Abstract :
This paper describes a novel system for detecting human activity based on multi-sensor approach. This approach aim to provide accuracy and robustness to the activity recognition system. The performances of the systems that fuse multiple data coming from different sources are deemed to benefit from the heterogeneity and the diversity of the information involved. In this work a novel Multi-Sensor Data Fusion (MSDF) architecture is presented. This applies an information fusion algorithm based Fuzzy Logic with a set of rules in order to recognize Human Behavior. So as to obtain Feature-level Fusion from Extraction of physical data.
Keywords :
behavioural sciences computing; fuzzy logic; sensor fusion; MSDF architecture; activity detection; activity recognition system; fuzzy logic; human behavior; information fusion; multisensor data fusion model; Data integration; Data models; Feature extraction; Fuzzy logic; Monitoring; Robot sensing systems; Senior citizens; Human Activity Detection; Information fusion; Multi-sensor data Fusion;
Conference_Titel :
ICT and Knowledge Engineering (ICT and Knowledge Engineering), 2014 12th International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4799-8025-3
DOI :
10.1109/ICTKE.2014.7001535