Smart Home Crawler: Towards a framework for semi-automatic IoT sensor integration

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(From the abstract)

Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and gateways, data integration is still a costly and time-consuming process. In this paper we propose the Smart Home Crawler Framework that (1) provides a common semantic abstraction from the underlying sensor and gateway technologies, and (2) accelerates the integration of new devices by applying machine learning techniques for linking discovered devices to a semantic data model. We present a first prototype that was demonstrated at ICT 2018. The prototype was built as a domain-specific crawling component for IoTCrawler, a secure and privacy-preserving search engine for the Internet of Things.

In this paper we have outlined our initial work on Smart Home Crawling, an approach for faster integration of IoT sensor data in the Smart Home domain. We address the heterogeneity problem by building on the IoTCrawler architecture and proposing an initial framework for Smart Home Crawling that we believe can be generalised to other domains of IoT crawling and semi-automatic IoT data integration.

Martin Strohbach, Luis Adan Saavedra, Pavel Smirnov, Stefaniia Legostaieva

AGT International

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