ForeSight - Platform Approach for Enabling AI-based Services for Smart Living

Bauer, Jakob; Hoffmann, Hilko; Feld, Thomas; Runge, Mathias; Hinz, Oliver; Mayr, Andreas; Förster, Kristina; Teske, Franz; Schäfer, Franziska; Konrad, Christoph; Franke, Jörg

doi:10.1007/978-3-030-32785-9_19

Cited by 4 publications

(8 citation statements)

References 10 publications

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“…Following the approach of [38] for qualitative content analysis, a fivestep evaluation concept was applied to the raw data in order to further transform the transcripts to answer the research questions and derive the relevant information to enhance our model. The evaluation concept consists of the following phases: (1) Determination of research questions and analysis perspective, (2) Development of a category system, (3) Search texts for relevant information and assign them to corresponding categories, (4) Aggregation of information over different interviews, (5) Analyzing the results to answer RQ2. Based on the concepts derived from the literature review, a category system was designed to encode the transcribed interviews.…”

Section: Expert Interviews and Qualitative Content Analysismentioning

confidence: 99%

“…One of the fastest growing data ecosystem is the "smart living mega ecosystem" [4] by extending the smart home concept beyond simple home automation. On a technological level, the cross-actor exchange of data and its utilization in AI technologies are of key importance [5]. Speech recognition, object identification or energy management are exemplary application fields of AI in the smart living domain.…”

Section: Introductionmentioning

confidence: 99%

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Integrating Data and Service Lifecycle for Smart Service Systems Engineering: Compilation of a Lifecycle Model for the Data Ecosystem of Smart Living

Kortum¹,

Rebstadt²,

Hagen³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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In smart service systems engineering, where actors rely on the mutual exchange of data to create complex and holistic solutions, integration is crucial. Nevertheless, the management of data as a driving resource still lacks organizational structure. There is no holistic lifecycle approach that integrates data and service lifecycle and adopts a cross-actor perspective. Especially in data ecosystems, where sovereign actors depend on the mutual exchange of data to create complex, but transparent service systems, an integration is of crucial importance. This particularly applies to the smart living domain, where different industries, products and services interact in a complex environment. In this paper we address this shortcoming by proposing an integrated model that covers the different relevant lifecycles based on a systematic literature review and supplement it by concrete domain requirements from the smart living ecosystem obtained through semi-structured expert interviews.

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Section: Expert Interviews and Qualitative Content Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrating Data and Service Lifecycle for Smart Service Systems Engineering: Compilation of a Lifecycle Model for the Data Ecosystem of Smart Living

Kortum¹,

Rebstadt²,

Hagen³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

“…Beyond smart homes, the term "smart living" ranges over various areas that are separated today concerning energy management, health and home automation [5]. The smart home is a core element in a connected world, as well as smart city and smart grid [6]. This will lead to more comfort, better assistance and increased safety and security as well as improved resource efficiency and reduced overall costs.…”

Section: Motivationmentioning

confidence: 99%

“…The ForeSight project follows the approach of an open platform which integrates AI-based solutions, interoperability, context-awareness and established building automation technologies into a flexible multi-domain and multicomponent system ranging across different manufacturers and industries [6]. Furthermore, ForeSight will provide the flexibility to add new services and offers corresponding tools for service providers.…”

Section: Supported By German Federal Ministry For Economic Affairs and Energymentioning

confidence: 99%

ForeSight - An AI-driven Smart Living Platform, Approach to Add Access Control to openHAB

Bauer

Hechtel

Konrad

et al. 2020

Lecture Notes in Computer Science

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We created an approach for a smart living platform called ForeSight which consists of different modules: a service engineering module, a Web of Things (WoT)-based Internet of Things (IoT) module and an artificial intelligence (AI) component. This paper describes how open-HAB, a smart home middleware, is extended to fulfill platform requirements related to a successful interaction with the IoT module of Fore-Sight, more precisely, to add identity and access management (IAM) to openHAB and comply with European privacy laws.

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“…These services take into account a large number of dynamic parameters, distributed data sources and behavior variants that need to be processed in near real-time. Developing suitable AI-methods will therefore be a key component of smart living services in order to meet user requirements [15,16].…”

Section: Concepts From the Smart Living Domainmentioning

confidence: 99%

Engineering of Data-Driven Service Systems for Smart Living: Application and Challenges

Kortum

Gravemeier

Zarvic

et al. 2020

IFIP Advances in Information and Communication Technology

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Service systems in the smart living domain integrate a multitude of heterogenous data sources and affect the most private area of human lives. Therefore, particular challenges for service systems engineering arise in terms of interoperability of Internet-of-Things (IoT)-devices, privacy concerns and creating truly smart value propositions. By applying a promising approach, this paper examines smart service systems engineering and reveals the potential for extensions and adaptations of existing methods. A need for the integration of data science and software engineering approaches as well as a focus on acceptance, usability and the business perspective within a holistic smart service systems engineering method is discussed. This enables smart service systems to reconcile their human-centered and data-driven qualities.

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ForeSight - Platform Approach for Enabling AI-based Services for Smart Living

Cited by 4 publications

References 10 publications

Integrating Data and Service Lifecycle for Smart Service Systems Engineering: Compilation of a Lifecycle Model for the Data Ecosystem of Smart Living

Integrating Data and Service Lifecycle for Smart Service Systems Engineering: Compilation of a Lifecycle Model for the Data Ecosystem of Smart Living

ForeSight - An AI-driven Smart Living Platform, Approach to Add Access Control to openHAB

Engineering of Data-Driven Service Systems for Smart Living: Application and Challenges

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