A survey of ambient intelligence

R Dunne, T Morris, S Harper - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Ambient Intelligence (AmI) is the application and embedding of artificial intelligence into
everyday environments to seamlessly provide assistive and predictive support in a multitude …

What we do–and don't–know about the Smart Home: an analysis of the Smart Home literature

S Solaimani, W Keijzer-Broers… - Indoor and Built …, 2015 - journals.sagepub.com
Technological innovations, from ubiquitous computing, augmented reality,
telecommunication to intelligent appliances and robotics, bring new possibilities to the Smart …

A sequential deep learning application for recognising human activities in smart homes

D Liciotti, M Bernardini, L Romeo, E Frontoni - Neurocomputing, 2020 - Elsevier
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 …

Activity recognition and anomaly detection in smart homes

LG Fahad, SF Tahir - Neurocomputing, 2021 - Elsevier
Physical and cognitive impairments decline the ability of elderly in execution of daily
activities, such as eating, sleeping or taking medication. The proposed approach recognizes …

Uncertainty-aware Action Decoupling Transformer for Action Anticipation

H Guo, N Agarwal, SY Lo, K Lee… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Human action anticipation aims at predicting what people will do in the future based on past
observations. In this paper we introduce Uncertainty-aware Action Decoupling Transformer …

CAP: Community activity prediction based on big data analysis

Y Zhang, M Chen, S Mao, L Hu, VCM Leung - IEEE network, 2014 - ieeexplore.ieee.org
Crowd sensing harnesses the power of the crowd by mobilizing a large number of users
carrying various mobile and networked devices to collect data with the intrinsic multi-modal …

[HTML][HTML] Predicting human behaviour with recurrent neural networks

A Almeida, G Azkune - Applied Sciences, 2018 - mdpi.com
As the average age of the urban population increases, cities must adapt to improve the
quality of life of their citizens. The City4Age H2020 project is working on the early detection …

Activity recognition using accelerometer sensor and machine learning classifiers

ASA Sukor, A Zakaria, NA Rahim - 2018 IEEE 14th …, 2018 - ieeexplore.ieee.org
Activity recognition is considered as an important task in many applications, particularly in
healthcare services. Among these applications include medical diagnostic, monitoring of …

Era: Expert retrieval and assembly for early action prediction

LG Foo, T Li, H Rahmani, Q Ke, J Liu - European Conference on Computer …, 2022 - Springer
Early action prediction aims to successfully predict the class label of an action before it is
completely performed. This is a challenging task because the beginning stages of different …

[HTML][HTML] Long-term activity recognition from wristwatch accelerometer data

E Garcia-Ceja, RF Brena, JC Carrasco-Jimenez… - Sensors, 2014 - mdpi.com
With the development of wearable devices that have several embedded sensors, it is
possible to collect data that can be analyzed in order to understand the user's needs and …