Context-aware scheduling algorithm in smart home system

2013 ◽  
Vol 10 (11) ◽  
pp. 155-164 ◽  
Author(s):  
Zheng Hong ◽  
Pan Li ◽  
Wang Jingxiao
Keyword(s):  
Smart Home ◽  
Scheduling Algorithm ◽  
Context Aware

scholarly journals A non-intrusive context-aware system for ambient assisted living in smart home

2013 ◽  
Vol 3 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Willy Allègre ◽  
Thomas Burger ◽  
Jean-Yves Antoine ◽  
Pascal Berruet ◽  
Jean-Paul Departe
Keyword(s):  
Assisted Living ◽  
Smart Home ◽  
Ambient Assisted Living ◽  
Context Aware ◽  
Context Aware System

A Differentially Private Context-Aware Edge-Cloud-Enabled Nursing System in Smart Home

2021 ◽  
Author(s):  
Gang-Ting Liu ◽  
Qi-Wen Li ◽  
Dan-Hong Wang ◽  
Ruo-Bing Ren ◽  
Hai-Tao Chou ◽  
...  
Keyword(s):  
Smart Home ◽  
Context Aware ◽  
Private Context

A Context-Aware Information Model for Elderly Homecare Services in a Smart Home

2009 ◽  
Author(s):  
Feng Zhou ◽  
Jianxin Roger Jiao ◽  
Songlin Chen ◽  
Daqing Zhang
Keyword(s):  
Home Environment ◽  
Smart Home ◽  
Rough Set Theory ◽  
Research Problem ◽  
Information Model ◽  
Context Aware ◽  
Sensor Platform ◽  
Smart Home Environment ◽  
Manual Assistance

One of the critical situations facing the society across the globe is the problem of elderly homecare services (EHS) due to the aggravation of the society coupled with diseases and limited social resources. This problem has been typically dealt with by manual assistance from caregivers and/or family members. The emerging Ambience Intelligence (AmI) technology suggests itself to be of great potential for EHS applications, owing to its strength in constructing a pervasive computing environment that is sensitive and responsive to the presence of human users. The key challenge of AmI implementation lies in context awareness, namely how to align with the specific decision making scenarios of particular EHS applications. This paper proposes a context-aware information model in a smart home to tackle the EHS problem. Mainly, rough set theory is applied to construct user activity models for recognizing various activities of daily living (ADLs) based on the sensor platform constructed in a smart home environment. Subsequently, issues of case comprehension and homecare services are also discussed. A case study in the smart home environment is presented. Initial findings from the case study suggest the importance of the research problem, as well as the feasibility and potential of the proposed framework.

Enablement of IoT Based Context-Aware Smart Home With Fog Computing

Fog Computing ◽  
2018 ◽  
pp. 251-263 ◽  
Author(s):  
Maggi Bansal ◽  
Inderveer Chana ◽  
Siobhan Clarke
Keyword(s):  
Smart Home ◽  
Fog Computing ◽  
Context Aware ◽  
Monitoring And Control ◽  
Context Processing ◽  
Context Aware Computing ◽  
Smart Lighting ◽  
Human In The Loop ◽  
Smart Appliances ◽  
Situational Information

The recent advent of Internet of Things (IoT), has given rise to a plethora of smart verticals- smart homes being one of them. Smart Home is a classic example of IoT, wherein smart appliances connected via home gateways constitute a local home network to assist people in activities of daily life. Smart Home involves IoT-based automation (such as smart lighting, heating, surveillance etc.), remote monitoring and control of smart appliances. Besides automation, human-in-the-loop is a unique characteristic of Smart home to offer personalized services. Understanding the human behavior requires context processing. Thus, enablement of Smart home involves two prominent technologies IoT and context-aware computing. Further, local devices lying in the smart home have the implicit location and situational information, hence fog computing can offer real-time smart home services. In this paper, the authors propose ICON (IoT-based CONtext-aware) framework for context-aware IoT applications such as smart home, further ICON leverages fog-based IoT middleware to perform context-aware processing.

Enablement of IoT Based Context-Aware Smart Home with Fog Computing

2017 ◽  
Vol 19 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Maggi Bansal ◽  
Inderveer Chana ◽  
Siobhan Clarke
Keyword(s):  
Smart Home ◽  
Fog Computing ◽  
Context Aware ◽  
Monitoring And Control ◽  
Context Processing ◽  
Context Aware Computing ◽  
Smart Lighting ◽  
Human In The Loop ◽  
Smart Appliances ◽  
And Control

The recent advent of Internet of Things (IoT), has given rise to a plethora of smart verticals- smart homes being one of them. Smart Home is a classic example of IoT, wherein smart appliances connected via home gateways constitute a local home network to assist people in activities of daily life. Smart Home involves IoT-based automation (such as smart lighting, heating, surveillance etc.), remote monitoring and control of smart appliances. Besides automation, human-in-the-loop is a unique characteristic of Smart home to offer personalized services. Understanding the human behavior requires context processing. Thus, enablement of Smart home involves two prominent technologies IoT and context-aware computing. Further, local devices lying in the smart home have the implicit location and situational information, hence fog computing can offer real-time smart home services. In this paper, the authors propose ICON (IoT-based CONtext-aware) framework for context-aware IoT applications such as smart home, further ICON leverages fog-based IoT middleware to perform context-aware processing.

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