A Survey of Ambient Intelligence

被引:40
作者
Dunne, Rob [1 ]
Morris, Tim [1 ]
Harper, Simon [1 ]
机构
[1] Univ Manchester, Dept Comp Sci, Kilburn Bldg,Oxford Rd, Manchester M13 9PL, Lancs, England
关键词
Human-computer interaction; smart environments; machine learning; PREDICTION; BEHAVIOR; ENVIRONMENTS; FRAMEWORK; PEOPLE;
D O I
10.1145/3447242
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Ambient Intelligence (AmI) is the application and embedding of artificial intelligence into everyday environments to seamlessly provide assistive and predictive support in a multitude of scenarios via an invisible user interface. These can be as diverse as autonomous vehicles, smart homes, industrial settings, and healthcare facilities-referred to as Ambient Assistive Living. This survey gives an overview of the field; defines key terms; discusses social, cultural, and ethical issues; and outlines the state of the art in AmI technology, and where opportunities for further research exist. We guide the reader through AmI from its inception more than 20 years ago, focussing on the important topics and research achievements of the past 10 years since the last major survey, before finally detailing the most recents research trends and forecasting where this technology is likely to develop. This survey covers domains, use cases, scenarios, and datasets; cultural concerns and usability issues; security, privacy, and ethics; interaction and recognition; prediction and intelligence; and hardware, infrastructure, and mobile devices. This survey serves as an introduction for researchers and the technical layperson into the topic of AmI and identifies notable opportunities for further research.
引用
收藏
页数:27
相关论文
共 109 条
  • [1] Abascal J., 2004, ACM's Special Interest Group on Computer-Human Interaction (SIGCHI), P1
  • [2] Acampora G, 2013, P IEEE, V101, P2470, DOI 10.1109/JPROC.2013.2262913
  • [3] Predicting Human Behaviour with Recurrent Neural Networks
    Almeida, Aitor
    Azkune, Gorka
    [J]. APPLIED SCIENCES-BASEL, 2018, 8 (02):
  • [4] Emotion-Aware Ambient Intelligence: Changing Smart Environment Interaction Paradigms Through Affective Computing
    Altieri, Alex
    Ceccacci, Silvia
    Mengoni, Maura
    [J]. DISTRIBUTED, AMBIENT AND PERVASIVE INTERACTIONS, 2019, 11587 : 258 - 270
  • [5] [Anonymous], 1978, OBEDIENCE AUTHORITY
  • [6] [Anonymous], 2015, ARXIV151108130
  • [7] Antonakakis M, 2017, PROCEEDINGS OF THE 26TH USENIX SECURITY SYMPOSIUM (USENIX SECURITY '17), P1093
  • [8] Apthorpe N., 2017, ARXIV170506805
  • [9] Prediction of appliances energy use in smart homes
    Arghira, Nicoleta
    Hawarah, Lamis
    Ploix, Stephane
    Jacomino, Mireille
    [J]. ENERGY, 2012, 48 (01) : 128 - 134
  • [10] Detecting indicators of cognitive impairment via Graph Convolutional Networks
    Arifoglu, Damla
    Charif, Hammadi Nait
    Bouchachia, Abdelhamed
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2020, 89