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Adaptive monitoring system for e-health smart homes

Haider Mshali, Tayeb Lemlouma, Damien Magoni
2018 Pervasive and Mobile Computing  
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

Albert Ali Salah, Theo Gevers, Nicu Sebe, Alessandro Vinciarelli
2011 Journal of Ambient Intelligence and Smart Environments  
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

Haider Hasan Mshali, Tayeb Lemlouma, Damien Magoni
2015 2015 IEEE International Conference on Data Science and Data Intensive Systems  
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

Meriem Zerkouk, Belkacem Chikhaoui
2020 Sensors  
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]

Lina Yao, Quan Z. Sheng, Boualem Benatallah, Schahram Dustdar, Xianzhi Wang, Ali Shemshadi, Anne H.H. Ngu
2017 arXiv   pre-print
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

Daqing Zhang, Bin Guo, Zhiwen Yu
2011 Computer  
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

H. Nakashima
2011 Kybernetes  
: 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

Jose Manuel Lopez-Guede, Aitor Moreno-Fernandez-de-Leceta, Alexeiw Martinez-Garcia, Manuel Graña
2015 BioMed Research International  
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

Jose Manuel Negrete Ramirez, Philippe Roose, Marc Dalmau, Yudith Cardinale
2018 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)  
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

Liliana I. Carvalho, Rute C. Sofia
2020 IoT  
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

Nikolaos Liappas, José Gabriel Teriús-Padrón, Rebeca Isabel García-Betances, María Fernanda Cabrera-Umpiérrez
2021 Sensors  
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

Samaneh Zolfaghari, Mohammad Reza Keyvanpour
2016 Proceedings of the 2016 Federated Conference on Computer Science and Information Systems  
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

Faouzi Sebbak, Farid Benhammadi
2016 Annales des télécommunications  
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]

Zachary Menter, Wei Zhong Tee, Rushit Dave
2021 Proceedings of International Joint Conference on Computational Intelligence  
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]

Oresti Banos, Muhammad Bilal Amin, Wajahat Ali Khan, Muhammad Afzel, Mahmood Ahmad, Maqbool Ali, Taqdir Ali, Rahman Ali, Muhammad Bilal, Manhyung Han, Jamil Hussain, Maqbool Hussain (+13 others)
2015 Lecture Notes in Computer Science  
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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