A Sequential Deep Learning Application for Recognising Human Activities in Smart Homes

TitleA Sequential Deep Learning Application for Recognising Human Activities in Smart Homes
Publication TypeJournal Article
Year of Publication2019
AuthorsLiciotti D, Bernardini M, Romeo L, Frontoni E
JournalNeurocomputing
ISSN0925-2312
KeywordsDeep Learning, Human Activity Recognition, LSTM, Smart Home
Abstract

The recent advancement and development of computer electronic devices has led to the adoption of smart home sensing systems, stimulating the demand for associated products and services. Accordingly, the increasingly large amount of data calls the machine learning (ML) field for automatic recognition of human behaviour. In this work, different deep learning (DL) models that learn to classify human activities were proposed. In particular, the long short-term memory (LSTM) was applied for modelling spatio-temporal sequences acquired by smart home sensors. Experimental results performed on the Center for Advanced Studies in Adaptive Systems datasets show that the proposed LSTM-based approaches outperform existing DL and ML methods, giving superior results compared to the existing literature.

URLhttp://www.sciencedirect.com/science/article/pii/S0925231219304862
DOI10.1016/j.neucom.2018.10.104