Smart Home Activities: A Literature Review

Al-Sumaiti, Ameena Saad; Ahmed, Mohammed Hassan; Salama, M.M.A.

doi:10.1080/15325008.2013.832439

Cited by 155 publications

(74 citation statements)

References 42 publications

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“…"Smart Home" is an intelligent home that would provide the fully automated quality of living, with multifunctional robots and smart devices. According to Ameena Saad et al (2014) [5], the primary objectives of a Smart Home are to increase home automation, facilitate energy management, and reduce environmental emissions. Home automation can be improved through an enhanced communication network that comprises a twisted pair power lines, radio signals, or fiber optics in a bus-based network or an internet protocol as standards.…”

Section: B Theoritical Backgroundmentioning

confidence: 99%

Smart Homes (Conceptual Views)

Madakam

Ramaswamy

2014

2014 2nd International Symposium on Computational and Business Intelligence

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Smart Homes (Intelligent Homes) are homes with technologically advanced systems to enable domestic task automation, easier communication and higher security. The applications that can be supported by a Smart Home are very wide and their degree of sophistication depends on the underlying technology used. Some of the application areas include automation, monitoring and control of appliances, security, telemedicine, entertainment, location based services, care for children and the elderly etc. This paper explores the concept of Smart Home paradigms and process. Moreover this study is a systematic review of Smart Homes and different academic projects handled by institutions across the world.

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Section: B Theoritical Backgroundmentioning

confidence: 99%

Smart Homes (Conceptual Views)

Madakam

Ramaswamy

2014

2014 2nd International Symposium on Computational and Business Intelligence

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“…The main potential is for a smart home system to control energy use during "lowusage" times of the day [3], [4]. The times that can be defined as low usage are when the family members are either at work or school as well as when they are sleeping.…”

Section: Introductionmentioning

confidence: 99%

DTLS for Lightweight Secure Data Streaming in the Internet of Things

Fisher

Hancke

2014

2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

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The huge number of sensors envisioned to be deployed within Internet of Things applications will result in large amounts of likely confidential data that will be required to traverse the open Internet. This confidential data could range from the current security status of a smart house to the current health status of an elderly person connected to smart monitors. A secure and able connection will be required to connect either a cloud based or an in-house server to the embedded sensors. The ability to ensure that the data generated by the sensor networks is securely streamed to the central server will allow for real time access to the data. The use of the less favoured Datagram Transport Layer Security protocol is compared with the widely used Transport Layer Security protocol. The research shows that Datagram Transport Layer Security is a capable alternative to Transport Layer Security when it comes to streaming data across the Internet from connected Wireless Sensor Networks.

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“…The increasing popularity of wearable computing sensing boosting devices, such as Google Glass, watches, helmets, shoes, etc., results in potential demands and opportunities for ubiquitous computing via wireless and mobile devices [5,6]. Meanwhile, mobile recommendation technology helps users to extract information which meets their requirements automatically and effectively from the vast ocean of available sensor information.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments

Chen

Xie

Shu

et al. 2016

Sensors

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With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates.

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Smart Home Activities: A Literature Review

Cited by 155 publications

References 42 publications

Smart Homes (Conceptual Views)

Smart Homes (Conceptual Views)

DTLS for Lightweight Secure Data Streaming in the Internet of Things

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments

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