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Towards Semantic Search in Building Sensor Data

Conference ·
OSTI ID:1822654
 [1]; ; ;
  1. University of Virginia; Computer Science, University of Virginia
This paper presents a search engine system for sensor time series data and metadata in the context of building management. It takes natural language queries as input, retrieves sensor time series data, ranks them with respect to their relevance to a given query, and visualizes the time series as search results. In addition, the system allows users to interact with the search results: they can define events of interest in the visualized results and search across sensor data for similar events, i.e., the search by example scheme. Quantitative evaluations and user studies demonstrate the value of this system for managing building sensor data.
Research Organization:
University of Virginia
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
DOE Contract Number:
EE0008227
OSTI ID:
1822654
Report Number(s):
DOE-UVA-0008227-4
Country of Publication:
United States
Language:
English

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