Abstract:
Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reducti...Show MoreMetadata
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.
Published in: 2019 Global IoT Summit (GIoTS)
Date of Conference: 17-21 June 2019
Date Added to IEEE Xplore: 22 July 2019
ISBN Information: