Capturing hotspots for constrained indoor movement

Authors:
Tanvir Ahmed;Torben Bach Pedersen;Hua Lu
Affiliations:
Aalborg University, Denmark;Aalborg University, Denmark;Aalborg University, Denmark
Venue:
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Year:
2013

Citing 5
Cited 0

Effective Density Queries on ContinuouslyMoving Objects

ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Graph Model Based Indoor Tracking

MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Traffic density-based discovery of hot routes in road networks

SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Modeling indoor space

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
A Data Warehouse Solution for Analyzing RFID-Based Baggage Tracking Data

MDM '13 Proceedings of the 2013 IEEE 14th International Conference on Mobile Data Management - Volume 01

Quantified Score

Hi-index	0.00

Visualization

Abstract

Finding the hotspots in large indoor spaces is very important for getting overloaded locations, security, crowd management, indoor navigation and guidance. The tracking data coming from indoor tracking are huge in volume and not readily available for finding hotspots. This paper presents a graph-based model for constrained indoor movement that can map the tracking records into mapping records which represent the entry and exit times of an object in a particular location. Then it discusses the hotspots extraction technique from the mapping records.