SESAME-S: Semantic Smart Home System for Energy Efficiency

Fensel, Dieter; Tomic, Slobodanka; Kumar, Vikash; Stefanovic, Milan; Aleshin, Sergey V.; Novikov, D. O.

doi:10.1007/s00287-012-0665-9

Cited by 59 publications

(35 citation statements)

References 6 publications

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“…notwithstanding the changes required in the user interfaces [15]. After an initial study into such systems, we believe that our approach provides a unique mix of the qualities (mentioned in detail in [17,20]) that can be practically used in mainstream smart building systems. By basing most of our decision based reasoning on semantic policies, and thereafter by proposing the policy adaptation technique as detailed in this paper, we ensure that even the services for such a system can be easily adapted across several installation sites and/or user preferences.…”

Section: State Of the Art In Home Automationmentioning

confidence: 99%

Context Based Adaptation of Semantic Rules in Smart Buildings

Kumar¹,

Fensel

Fröhlich

2013

Proceedings of International Conference on Information Integration and Web-Based Applications &Amp; Services

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This paper presents a semantic policy adaptation technique and its applications in the context of smart building setups. We study how semantic rules which are created for one set of contextual conditions are affected when one of the context parameters changes. In particular, rules for triggering alerts and monitoring appliances and their adaptation with changing contexts have been studied in detail. We then describe how this changing context triggers changes in other related context parameters. This technique has been implemented to demonstrate its feasibility, evaluated and positively accepted during trials with users of a real-life semantically empowered smart building setup.

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Section: State Of the Art In Home Automationmentioning

confidence: 99%

Context Based Adaptation of Semantic Rules in Smart Buildings

Kumar¹,

Fensel

Fröhlich

2013

Proceedings of International Conference on Information Integration and Web-Based Applications &Amp; Services

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“…They built an experimental testbed for energy consumption data analysis. Fensel et al [263] proposed the SESAME-S project (SEmantic SmArt Metering -Services for energy efficient houses). The project focuses on designing and evaluating the energy efficiency services to enable the end-consumers in making the right decisions and controlling their energy consumption.…”

Section: ) Apache Flume: Flumementioning

confidence: 99%

Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

et al. 2019

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Future buildings will offer new convenience, comfort, and efficiency possibilities to their residents. Changes will occur to the way people live as technology involves into people's lives and information processing is fully integrated into their daily living activities and objects. The future expectation of smart buildings includes making the residents' experience as easy and comfortable as possible. The massive streaming data generated and captured by smart building appliances and devices contains valuable information that needs to be mined to facilitate timely actions and better decision making. Machine learning and big data analytics will undoubtedly play a critical role to enable the delivery of such smart services. In this paper, we survey the area of smart building with a special focus on the role of techniques from machine learning and big data analytics. This survey also reviews the current trends and challenges faced in the development of smart building services.

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“…Previous research on the smart home simulator has been focused primarily on saving energy [3], [4]. A research to improve energy efficiency for smart building is presented in [5].…”

Section: Related Workmentioning

confidence: 99%

A Smart Home Network Simulation Testbed for Cybersecurity Experimentation

Tong

Sun

Wang

2014

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. With the rapid development of smart home, it becomes essential to study techniques to safeguard the home area network (HAN) against various security attacks. In this paper, a smart home network simulation testbed has been developed for security research in this area. It is designed to feature high fidelity, cost-effectiveness and user-friendliness. The testbed enables users to specify the HAN network topology, communication protocols and appliances, as well as develop security mechanisms such as information flow tracking. For the evaluation purpose, two security mechanisms were implemented on the testbed and their effectiveness against attacks is studied using the developed testbed.

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SESAME-S: Semantic Smart Home System for Energy Efficiency

Cited by 59 publications

References 6 publications

Context Based Adaptation of Semantic Rules in Smart Buildings

Context Based Adaptation of Semantic Rules in Smart Buildings

Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

A Smart Home Network Simulation Testbed for Cybersecurity Experimentation

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