Simulation of Smart Environments

Armac, Ibrahim; Retkowitz, Daniel

doi:10.1109/perser.2007.4283934

Cited by 16 publications

(10 citation statements)

References 7 publications

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“…Currently, we are adapting the final deployment phase of the SCD-process to connect our tool to the eHomeSimulator [6], which is a virtual eHome environment we use as a testbed. This enables us to simulate environments containing numerous different devices and to evaluate more complex scenarios and the dynamic behavior at runtime.…”

Section: Discussionmentioning

confidence: 99%

“…The scenario presented above requires e. g. some means of automated person and device detection. The demonstration environments described in [4] and [6], which we use as testbeds, provide these capabilities e. g. by means of video cameras or remote controls for the different users to log in. We assume that appropriate technologies will be available for future eHomes at low prices.…”

Section: Continuous Scd-processmentioning

confidence: 99%

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Dynamic Adaptability for Smart Environments

Retkowitz

Stegelmann

2008

Distributed Applications and Interoperable Systems

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Abstract. Software reuse and hardware integration are key factors to offer flexible, low-cost smart environments. Until now, we have been using a static process called the SCD-process to allow a tool-supported realization of such smart environments. The SCD-process is comprised of three different phases: specification, configuration, and deployment. As an initially specified environment is expected to change during runtime and the user may wish to influence certain aspects of the configuration, the static process had to be adapted. This paper describes a new process that supports continuous specification activities and allows for an automated adaptation of the smart home's configuration based on a model-driven approach. We enriched the specification of services with binding policies and constraints to allow for a flexible reconfiguration and a service-specific adaptation. The new configuration mechanism facilitates dynamic reconfiguration based on context information and the extended service specification. In addition, we present a visual tool, which is used to assist the developer and the end-user.

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Section: Discussionmentioning

confidence: 99%

Section: Continuous Scd-processmentioning

confidence: 99%

Dynamic Adaptability for Smart Environments

Retkowitz

Stegelmann

2008

Distributed Applications and Interoperable Systems

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“…The described mechanism has been implemented and integrated into our prototype system. So far, we only performed a qualitative validation based on the eHomeSimulator, a software tool we developed to simulate different smart environments [7]. The results show that our approach actually allows to resolve resource conflicts.…”

Section: Fig 3 Connection Between Services Functions and Prioritiesmentioning

confidence: 99%

Dependency Management in Smart Homes

Retkowitz

Kulle

2009

Distributed Applications and Interoperable Systems

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In future smart homes functionality will be provided to the inhabitants by software services decoupled from the underlying hardware devices. While this will enhance flexibility and will allow to provide cross-functionalities across multiple devices it will also lead to resource conflicts. Future devices will provide basic functionalities which are used by separate higher level services. Each person will use a number of different services and each environment can be inhabited by multiple users at the same time. All respective services have to be executed based on a limited number of devices, which will result in resource conflicts. In this paper we describe how we extended our existing dependency management approach for smart home services with a mechanism for monitoring service bindings and handling access control based on priority groups.

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“…Acquisition of such datasets is subject to limitations for a number of reasons [ 5 ]. Physical IEs are expensive to implement due to the cost of the sensor technology and the construction of the physical environments [ 5 , 45 , 49 , 50 , 51 ]. Additionally, the construction of such environments is a time consuming process requiring considerable groundwork before commitment to the purchase of equipment for the environment construction [ 52 ].…”

Section: Introductionmentioning

confidence: 99%

“…This requires considerable time and expense and may be impractical in real-world implementations where significant alterations to the environment may lead to distress or confusion, particularly to inhabitants suffering from conditions such as dementia [ 52 ]. These environments therefore lack flexibility [ 51 , 53 ] and may have limited scalability [ 51 ]. As a result of these costs and constraints, not all researchers have direct access to such environments and the datasets they produce.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Smart Home Activity Datasets

Synnott

Nugent

Jeffers³

2015

Sensors

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A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

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Simulation of Smart Environments

Cited by 16 publications

References 7 publications

Dynamic Adaptability for Smart Environments

Dynamic Adaptability for Smart Environments

Dependency Management in Smart Homes

Simulation of Smart Home Activity Datasets

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