1 / 13

The Emergence of GeoSensor Networks

The Emergence of GeoSensor Networks. Anthony Stefanidis. Dept. of Spatial Information Science & Engineering University of Maine Ph:(207) 581-2180 or (207) 581 2127 E- mail: tony@spatial.maine.edu http://www.spatial.maine.edu/~tony. Outline. Sensor Networks GeoSensor Networks

catrin
Download Presentation

The Emergence of GeoSensor Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Emergence of GeoSensor Networks Anthony Stefanidis Dept. of Spatial Information Science & Engineering University of Maine Ph:(207) 581-2180 or (207) 581 2127 E- mail: tony@spatial.maine.edu http://www.spatial.maine.edu/~tony

  2. Outline • Sensor Networks • GeoSensor Networks • Distributed Video Surveillance Applications • Concluding Remarks

  3. Snadia Lab’s SnifferSTAR Mica2 Sensor Platform Sensor Networks • Networks of collaborating sensing and computing devices. • Heterogeneous devices with various levels of capabilities. Small (mm3 - cm3), unobtrusive, expendable, cost-effective. • Wireless technology, nanotechnology, databases

  4. Sensor Networks (cont.) • Hierarchical organization • Application-specific in-network sensor collaboration (Hill et al., CACM)

  5. GeoSensor Networks • Monitoring is aware of the geographic space within which phenomena evolve • Geospatial component of information is important in terms of content and analysis

  6. GeoSensor Networks: An Evolution in Data Collection • From homogeneous data collections (e.g. aerial photos) to heterogeneous feeds (e.g. video and temperature) • From regularly sampled datasets to fragments of information that vary in distribution, accuracy, … • From spatial to spatiotemporal information

  7. GSN Example Case: Distributed Video-Based Surveillance • Trends in imagery collection: from static to motion and from single to multiple sensors. • Tremendous amounts of data. • Bottleneck in the analyst workforce.

  8. Distributed Video-Based Surveillance: Needs • Efficient algorithms for object tracking in single feeds • Linking information across feeds • Identification of interesting spatiotemporal activities and support for intelligent queries • Communication of captured information

  9. From Video Feeds to Spatiotemporal Queries The results are shown in a GIS layer or the video.

  10. From Video Feeds to Spatiotemporal Queries: Activity Labeling

  11. VR Query Interface SmartSensorNode SmartSensorNode DB SmartSensorNode SmartSensorNode Video streams Object Extraction Visualization: Towards Virtual GeoReality (VGR)

  12. Concluding Remarks • The emergence of geosensor networks is revolutionizing geospatial data collection, information analysis, and communication • GSN’06: Fall 2006, Boston • GSN’03: www.amazon.com

More Related