… such as, elder care, ambient assisted living and smart home. Authors in Bianchi et al. (2019) …
An optimal feature vector is thus generated to be used in the SVM classifier for classification…

… For example, Sakorn and Anuchit [32] proposed a generic system for HAR in smart homes
using smartphone data. The proposed system is based on four LSTM networks to study the …

… A genetic algorithm based feature selection strategy is proposed that integrates with the
Multi-Instance Multi-Label kNN (k-nearest neighbor) for classification of optimal set of feature …

… for smart home applications such as activity recognition, data … smart home devices and
delivering them the most optimal … generated by meta-learner algorithm based on the input of first …

… Therefore, this research aims to propose a hybrid feature selection technique for optimal
human activities recognition. The methodology proposed for this research is the Ensemble Filter …

… smart home environments. The primary objective of human activity recognition in smart
home … selection algorithm based on particle swarm optimization for support vector machine …

… The RCNN-BiGRU is optimized for sensor-based human activity classification… activity
recognition (HAR), including healthcare and medical diagnosis, sports injury detection, smart home…

… (1) Activity recognition framework: considering feature subset selection influences the
appropriate classifier … HAR framework that can optimize the feature set and the parameters of the …

… fication of activities of daily living in health smart homes using … A survey on human activity
recognition and classification. In … A map matching algorithm based on a particle filter. In 2014 …

… Activity recognition is relevant to the smart home model. For helping different emergency-related
wellbeing services, such as fall detection for … algorithm-based optimal feature selection. …