LIGHTWEIGHT PRIORITY SCHEDULING SCHEME FOR SMART HOME AND AMBIENT ASSISTED LIVING SYSTEM

Author(s):  
Hamdan Sayuti ◽  
Author(s):  
Robert Radziszewski ◽  
Hubert Kenfack Ngankam ◽  
Vincent Grégoire ◽  
Dominique Lorrain ◽  
Hélène Pigot ◽  
...  

Purpose Assistive living technologies provide support for specific activities, transforming a home into a smart home. The purpose of this paper is to present how to design, implement, deploy and install a personalized ambient support system for the elderly suffering from Alzheimer’s disease (AD) and nighttime wandering. Design/methodology/approach The intervention presented in this paper proceeds in two phases. During the monitoring phase, the system determines the profile of the person with AD, based on nighttime routines. Data are gathered from sensors dispatched in the smart home, coupled with physiological data obtained from sensors worn by the person. Data are then classified to determine engine rules that will provide assistance to the resident to satisfy their needs. During the second phase, smart assistance is provided to the person via environmental cues by triggering rules based on the person’s habits and the activities occurring during night. Findings The paper develops the architecture of a non-intrusive system that integrates heterogeneous technologies to provide a calm environment during night and limit wandering periods. Practical implications The goal is to help people age well at home as long as possible and recover a regular circadian cycle while providing more comfort to the caregiver. Originality/value The system presented in this paper offers a calm and personalized environment with music and visual icons to soothe persons with AD and encourage them to go back to bed. It is installed at the patient’s home using wireless technologies.


2013 ◽  
Vol 3 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Willy Allègre ◽  
Thomas Burger ◽  
Jean-Yves Antoine ◽  
Pascal Berruet ◽  
Jean-Paul Departe

2018 ◽  
Vol 7 (2.19) ◽  
pp. 52
Author(s):  
J Vivek ◽  
Gandla Maharnisha ◽  
Gandla Roopesh Kumar ◽  
Ch Karun Sagar ◽  
R Arunraj

In  this  paper,  context  awareness  is  a  promising  technology  that  provides  health care services and a niche  area of big data paradigm. The   drift  in  Knowledge  Discovery  from  Data  refers  to  a  set  of  activities  designed  to refine and  extract  new knowledge from complex  datasets.  The   proposed  model  facilitates  a  parallel  mining  of  frequent item sets for Ambient Assisted Living (AAL) System [a.k.a. Health  Care [System]  of  big  data that  reside   inside  a  cloud  environment.  We  extend  a  knowledge  discovery framework for  processing  and  classifying  the  abnormal  conditions of patients having fluctuations in Blood Pressure (BP) and Heart Rate(HR) and storing  this data  sets  called  Big data  into Cloud to access from  anywhere   when  needed.   This   accessed data is used to compare the new data with it, which helps to know the patients health condition.  


2020 ◽  
pp. 793-821 ◽  
Author(s):  
Dulce Domingos ◽  
Ana Respício ◽  
Ricardo Martinho

BPMN (Business Process Model and Notation) has become the de-facto business process modelling language standard. Healthcare processes have been increasingly incorporating participants other than humans, including Internet of Things (IoT) physical devices such as biomedical sensors or patient electronic tags. Due to its critical requirements, IoT-aware healthcare processes justify the relevance of Quality of Services aspects, such as reliability, availability, and cost, among others. This chapter focuses on reliability and proposes to use the Stochastic Workflow Reduction (SWR) method to calculate the reliability of IoT-aware BPMN healthcare processes. In addition, the chapter proposes a BPMN language extension to provide processes with reliability information. This way, at design time, modellers can analyse alternatives and, at run time, reliability information can be used to select participants, execute services, or monitor process executions. The proposal is applied to an Ambient Assisted Living system use case, a rich example of an IoT-aware healthcare process.


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