Title

GruMon: Fast and Accurate Group Monitoring for Heterogeneous Urban Spaces

Publication Type

Conference Proceeding Article

Publication Date

11-2014

Abstract

Real-time monitoring of groups and their rich contexts will be a key building block for futuristic, group-aware mobile services. In this paper, we propose GruMon, a fast and accurate group monitoring system for dense and complex urban spaces. GruMon meets the performance criteria of precise group detection at low latencies by overcoming two critical challenges of practical urban spaces, namely (a) the high density of crowds, and (b) the imprecise location information available indoors. Using a host of novel features extracted from commodity smartphone sensors, GruMon can detect over 80% of the groups, with 97% precision, using 10 minutes latency windows, even in venues with limited or no location information. Moreover, in venues where location information is available, GruMon improves the detection latency by up to 20% using semantic information and additional sensors to complement traditional spatio-temporal clustering approaches. We evaluated GruMon on data collected from 258 shopping episodes from 154 real participants, in two large shopping complexes in Korea and Singapore. We also tested GruMon on a large-scale dataset from an international airport (containing ≈37K+ unlabelled location traces per day) and a live deployment at our university, and showed both GruMon's potential performance at scale and various scalability challenges for real-world dense environment deployments.

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

SenSys '14: Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems: November 3-6, 2014, Memphis, TN

First Page

46

Last Page

60

ISBN

9781450331432

Identifier

10.1145/2668332.2668340

Publisher

ACM

City or Country

New York

Additional URL

http://dx.doi.org/10.1145/2668332.2668340