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Adaptive monitoring system for e-health smart homes
2018
Pervasive and Mobile Computing
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We propose a new context-aware e-health monitoring system targeted at the elderly and isolated persons living alone. ...
It is then able to detect risky behavioral changes by using our novel forecasting approach based on the extension of the Grey model GM(1, 1). ...
Future work includes extending the number of actions considered in our scenario generation in order to refine our knowledge of a person's behavior. ...
doi:10.1016/j.pmcj.2017.11.001
fatcat:2onalchyizcclgnarqej5xlf6y
Computer vision for ambient intelligence
2011
Journal of Ambient Intelligence and Smart Environments
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Computer vision is an essential part of building contextaware environments that adapt and anticipate their human users by understanding their behavior. ...
A natural way of conceptualizing ambient intelligence is by picturing an active environment with access to perceptual input, not via eyes and ears, but by their technological counterparts. ...
Monitoring human behavior in an AAL application is not restricted to activities of daily living (ADL), but includes detection of falls, abnormal events, elopement (a concern for elderly with memory issues ...
doi:10.3233/ais-2011-0113
fatcat:spgxpoqu5nhdvccdksvxwreipa
Context-Aware Adaptive Framework for e-Health Monitoring
2015
2015 IEEE International Conference on Data Science and Data Intensive Systems
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For improving e-health services, we propose a context-aware framework to monitor the activities of daily living of dependent persons. ...
We define a strategy for generating long-term realistic scenarios and a framework containing an adaptive monitoring algorithm based on three approaches for optimizing resource usage. ...
We have proposed in this paper, a context-aware adaptive framework for monitoring the activities of elderly daily living. ...
doi:10.1109/dsdis.2015.13
dblp:conf/dsdis/MshaliLM15
fatcat:qfbgax5uwff7llaxhyrxzkezkm
Spatio-Temporal Abnormal Behavior Prediction in Elderly Persons Using Deep Learning Models
2020
Sensors
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Specifically, for elderly persons wishing to maintain their independence and comfort in their living spaces, abnormal behaviors observed during activities of daily living are a good indicator that the ...
The ability to identify and accurately predict abnormal behavior is important for health monitoring systems in smart environments. ...
The crucial goal is to create a better world for human beings, in which the objects around us are context-aware, allowing them to respond to questions such as what we want, what we need and where we are ...
doi:10.3390/s20082359
pmid:32326349
fatcat:5t2vq5okszer7eyamx35ismzxe
Up in the Air: When Homes Meet the Web of Things
[article]
2017
arXiv
pre-print
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WITS enables an unobtrusive monitoring of elderly people in a real-world, inhabituated home environment, by leveraging WoT technologies in building context-aware, personalized services. ...
Our system provides a layered framework for managing and sharing the information produced by physical things as well as the residents. ...
in home environments, so as to continuously track residents' daily behaviors and detect any abnormal events for early and timely medical assistance. ...
arXiv:1512.06257v3
fatcat:s66vfz66uvd57igaki3dozsoly
The Emergence of Social and Community Intelligence
2011
Computer
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With advances in computing, storage, Internet access, wireless communication, and sensing, it is now possible to monitor and analyze human behavior, social interactions, and city dynamics on a large scale ...
A group from the University of Koblenz-Landau has investigated how to mine social networks to study customer behavior. 1 Researchers from Purdue University have developed an unsupervised model to estimate ...
human behavior detection, health-status monitoring, and social-context recognition. ...
doi:10.1109/mc.2011.65
fatcat:ati2z2ncnng45hxobax4t7vsga
Handbook of Ambient Intelligence and Smart Environments20114Handbook of Ambient Intelligence and Smart Environments. Berlin: Springer 2010. $229.00 (hardcover) xviii, 1294 pp. (100 illustr.) 974‐0‐387‐93807
2011
Kybernetes
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: AI Decision Making . . . . . . . . . 681
4.2
Application Model (B): Abnormal Behavior Detection . 682
4.3
Application Model (C): Enabling "Smart Environments" 686
4.4
Application Model (D): Environment ...
Monitoring for Physical
. 603
Spatio-Temporal Reasoning and Context
. 663
Behavior Modeling for Detection, Identification, Prediction, and Reaction (DIPR) in AI Systems
. 839
Smart Offices ...
Today different appliances have successfully become integrated to our daily life surroundings to such an extent that we use them without consciously thinking about them. ...
doi:10.1108/03684921111169602
fatcat:vzpxididpfb5lceysolr3sjd6a
Lynx: Automatic Elderly Behavior Prediction in Home Telecare
2015
BioMed Research International
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If the system detects that something unusual happens (in a wide sense) or if something is wrong relative to the user's health habits or medical recommendations, it sends at real-time alarm to the family ...
This paper introduces Lynx, an intelligent system for personal safety at home environments, oriented to elderly people living independently, which encompasses a decision support machine for automatic home ...
Thanks are due to the Onkologikoa (http://www.onkologikoa.com/) medical staff for their support regarding the medical summaries validations. ...
doi:10.1155/2015/201939
pmid:26783514
pmcid:PMC4689880
fatcat:2pm6tquoxfebvpszycdaeogzb4
An event detection framework for the representation of the AGGIR variables
2018
2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
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To model the Activities of Daily Living (ADL), we also extend a previously proposed Domain Specific Language (DSL), in order to employ operators to deal with constraints related to time and location of ...
In this paper, we propose a framework to study the AGGIR (Autonomy Gerontology Iso-Resources Groups) grid model, in order to evaluate the level of independency of elderly people, according to their capabilities ...
AICOs is able to classify human activities of daily living and to identify how many activities can be detected simultaneously using a Bayesian-Network-based fusion engine. ...
doi:10.1109/wimob.2018.8589105
dblp:conf/wimob/RamirezRDC18
fatcat:cryuf5zyyvdgzb5q5xg3bzvzva
A Review on Scaling Mobile Sensing Platforms for Human Activity Recognition: Challenges and Recommendations for Future Research
2020
IoT
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This review paper contributes to raising awareness of challenges faced today by mobile sensing platforms that perform learning and behavior inference with respect to human routines: how current solutions ...
The paper provides a set of guidelines that contribute to a better functional design of mobile sensing infrastructures, keeping scalability as well as interoperability in mind. ...
With automatic context recognition, it is possible, for instance, to detect abnormal patterns, e.g., isolation of a user, falls, etc. [92] [93] [94] . ...
doi:10.3390/iot1020025
fatcat:j5doqye55bfa3oj6derzmszsha
Advancing Smart Home Awareness—A Conceptual Computational Modelling Framework for the Execution of Daily Activities of People with Alzheimer's Disease
2021
Sensors
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during the daily life of a person living with cognitive deterioration. ...
This paper presents a conceptual computational framework for the modelling of daily living activities of people with AD and their progression through different stages of AD. ...
We would like to thank the ACROSSING consortium for the valuable scientific knowledge that was produced. ...
doi:10.3390/s22010166
pmid:35009709
pmcid:PMC8747630
fatcat:3jrvwblwhjbqbgxjjtbiizhery
SARF: Smart Activity Recognition Framework in Ambient Assisted Living
2016
Proceedings of the 2016 Federated Conference on Computer Science and Information Systems
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A review of the literature reveals various approaches to discovering and recognizing human activities. ...
Human activity recognition in Ambient Assisted Living (AAL) is an important application in health care systems and allows us to track regular activities or even predict these activities in order to monitor ...
of Daily Living (ADL) in smart homes, especially due to the rapid growth of elderly population, in surveillance and security environments to automatic detection of abnormal activities to alert the relevant ...
doi:10.15439/2016f132
dblp:conf/fedcsis/ZolfaghariK16
fatcat:77entfwdtvfp3autxkgfszwbse
Majority-consensus fusion approach for elderly IoT-based healthcare applications
2016
Annales des télécommunications
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With the recent advancements in IoT-based healthcare technologies, activity recognition can be used as the key part of the intelligent healthcare systems to monitor elderly people to live independently ...
at homes and promote a better care. ...
So, several attempts have been proposed to avoid this abnormal behavior. ...
doi:10.1007/s12243-016-0550-7
fatcat:msossqngp5dwrb7hjzmoenxk5y
Application of Machine Learning-Based Pattern Recognition in IoT Devices: Review
[chapter]
2021
Proceedings of International Joint Conference on Computational Intelligence
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2022 pre-print arXiv:2202.02456v1 fatcat:mwwbfsvjcbfhxf5owhuoxvkt4y
With greater numbers of everyday objects being connected to the Internet, many different innovations have been presented to make our everyday lives more straightforward. ...
After reviewing the applications of different machine learning algorithms, results vary from case to case, but a general conclusion can be drawn that the optimal machine learning-based pattern recognition ...
This is known as activity aware human context recognition (AAHCR). Daily Living Activities (DLAs) used in the proposed scheme include lying down, running, sitting, standing and walking.
Fig. 1. ...
doi:10.1007/978-981-16-3246-4_52
fatcat:ipb2x4ayhberbdctmfsgp475le
An Innovative Platform for Person-Centric Health and Wellness Support
[chapter]
2015
Lecture Notes in Computer Science
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Modern digital technologies are paving the path to a revolutionary new concept of health and wellness care. ...
This work introduces Mining Minds, an innovative framework that builds on some of the most prominent modern digital technologies, such as Big Data, Cloud Computing, and Internet of Things, to enable the ...
It is composed by two sublayers, namely, Low Level Context Awareness (LLCA) and High Level Context Awareness (HLCA). ...
doi:10.1007/978-3-319-16480-9_14
fatcat:45o5q5u5ibgqxlnqoyu3ufx4ve
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