Spatial indexing for data searching in mobile sensing environments

Yuchao Zhou, Suparna De*, Wei Wang, Klaus Moessner, Marimuthu S. Palaniswami

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.

Original languageEnglish
Article number1427
JournalSensors (Switzerland)
Volume17
Issue number6
DOIs
Publication statusPublished - 18 Jun 2017

Keywords

  • Mobile sensing
  • Mobile sensor data search
  • Opportunistic sensing
  • Spatial indexing
  • Web of Things (WoT)

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