IDiary: From GPS signals to a text-searchable diary

Dan Feldman, Andrew Sugaya, Cynthia Sung, Daniela Rus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a system that takes as input GPS data streams generated by users' phones and creates a searchable database of locations and activities. The system is called iDiary and turns large GPS signals collected from smart-phones into textual descriptions of the trajectories. The system features a user interface similar to Google Search that allows users to type text queries on their activities (e.g.,\Where did I buy books?") and receive textual answers based on their GPS signals. iDiary uses novel algorithms for semantic compression (known as coresets) and trajectory clustering of massive GPS signals in parallel to compute the critical locations of a user. Using an external database, we then map these lo-cations to textual descriptions and activities so that we can apply text mining techniques on the resulting data (e.g. LSA or transportation mode recognition). We provide experimental results for both the system and algorithms and compare them to existing commercial and academic state-of-the-art. This is the first GPS system that enables text-searchable activities from GPS data.

Original languageEnglish
Title of host publicationSenSys 2013 - Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery
Pages6:1-6:12
ISBN (Print)9781450320276
DOIs
StatePublished - 2013
Externally publishedYes
Event11th ACM Conference on Embedded Networked Sensor Systems, SenSys 2013 - Rome, Italy
Duration: 11 Nov 201315 Nov 2013

Publication series

NameSenSys 2013 - Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems

Conference

Conference11th ACM Conference on Embedded Networked Sensor Systems, SenSys 2013
Country/TerritoryItaly
CityRome
Period11/11/1315/11/13

Keywords

  • Activity recognition
  • GPS
  • Mobile device
  • Semantic compression
  • Text query

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Fingerprint

Dive into the research topics of 'IDiary: From GPS signals to a text-searchable diary'. Together they form a unique fingerprint.

Cite this