Title:SGER: Detecting and Maintaining Evolving Regions from Spatially and Temporally Varying Observations for Monitoring and Alerting
Last updated: August 23, 2010
Principle Investigator: Yan Huang (email@example.com)
Undergraduate student: Hector Cuellar, Alan Barbosa
Pre-college teachers : Dawn Chegwidden; Donn Arnold; Laura De Lemos; Sharon Wood
This material is based upon work supported by the National Science Foundation under Grant No. 0844342. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).
With the proliferation of wireless sensor networks and mobile
devices enabled by global positioning systems (GPSs), the volume of real-time
geo-referenced streams being collected is large and continues to increase.
Individual readings from sensors represent discrete sampling points, whereas
the phenomena that sensor networks monitor (e.g., floods, fires, and ocean
currents) are often spatially and temporally continuous.
This project aims at bridging the impedance mismatch of discrete sensor readings and the continuous phenomena. Specifically, we will explore incremental methods to detect and maintain evolving regions from discrete sensor readings in real time. This task is challenging and risky because (1) human intervention, which is important for region detection, needs to be minimal for the targeted monitoring applications; and (2) the alerting nature requires real-time responses, especially in disastrous situations when volumes of data are often high. The quality of service (QoS) requirement in terms of response time and accuracy of the regions detected needs to be balanced.
A novel idea of virtual sensor insertion will be explored to improve the accuracy of region detection. To reduce human intervention, the system will be equipped with a learning ability by using and maintaining statistics needed for incremental polygonization. Measurements in information retrieval will be explored creatively for identifying qualitative region evolvements and creating region evolvement graph, which will result in a reduced number of alerts sent to users.
The expected results will bridge the semantic gap of discrete readings and natural phenomena as well as provide a foundation for future work in geo-stream processing. Once the results are integrated into a geo-stream processing system, users can monitor evolving regions without being confined to querying discrete readings. The work will help sustain the growth of and support important time-critical applications such as disaster response and surveillance. Graduate students will be trained on various aspects of geo-stream processing. The project Web site (http://www.cse.unt.edu/~huangyan/eRegion) will be used for results dissemination.
1. An Integrated Web-based Content Management System for Environmental Observatory, Chengyan Zhang, Yan Huang, Miguel Acevedo, submitted to a journal
2. Efficient Algorithms for Interval-Based Nearest Neighbor Queries Over Sliding Windows from Trajectory Data , Chengyang Zhang and Yan Huang, Submitted to a journal
3. Low Cost Region Detection from Distributed Sensor Observations, Chengyang Zhang, Yan Huang, in proceedings of the 11th International Conference on Mobile Data Management, 2010
4. Demo Paper: Querying Geospatial Data Streams in Secondo, Chengyang Zhang, Yan Huang, Terry Griffin, in proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2009
5. Interval-Based Nearest Neighbor Queries Over Sliding Windows from Trajectory Data, Yan Huang, Chengyang Zhang, in proc. of The 10th International Conference on Mobile Data Management (MDM) , Pages 212-221, 2009
6. Remote Near-Real-Time Environmental Monitoring with Integrated Wired and Wireless Sensors, Jue Yang, Chengyang Zhang, Xinrong Li, Yan Huang, Shengli Fu, Miguel Acevedo, Springer/ACM Wireless Networks, DOI: 10.1007/s11276-009-0190-1, June 2009
7. Towards A Real and Remote Wireless Sensor Network Testbed, Shu Chen and Yan Huang and Chengyang Zhan, in Proc. of International Conference on Wireless Algorithms, Systems and Applications , Pages 385-396, 2008
8. New Data Types and Operations to Support Geo-streams, Yan Huang, Chengyang Zhang, in proc. of 5th International Conference on Geographic Information Science (GI Science), Pages: 106 - 118, 2008
9. An Environmental Monitoring System with Integrated Wired and Wireless Sensors, Jue Yang, Chengyang Zhang, Xinrong Li, Yan Huang, Shengli Fu, Miguel Acevedo , in Proc. of International Conference on Wireless Algorithms, Systems and Applications , Pages 224-236, 2008
Academic services: Dr. Yan Huang is:
· Treasurer : ACMGIS 2007, ACMGIS 2008, ACM SIGSpatial GIS 2009, ACM SIGSpatial GIS 2010
· Publicity Chair : FSKD 2007, WASA 2009
· Program Committee Member for the following conferences and workshops: International Workshop on GeoStreaming (IWGS), DKSS 2010, CIKM 2010, APSIPA 2010, ISI 2010, ACM SIGSpatial GIS 2010, ACM SIGSpatial GIS 2009 (treasurer), ICMLA 2009, DEXA 2009, ICDM 2009, SNAS'09 - Workshop on Social Networks, Applications, and Systems, First International Workshop on Data Warehousing and Knowledge Discovery from Sensors and Streams (DKSS 2009), ISI 2009, APWeb-WAIM 2009, SDM 2009, GEOWS 2009, ICMLA 2008, WASA 2008, KDE 2008, IADIS ECDM 2008, FSKD 2008, ACMGIS 2008 (treasurer), MDMM 2008
Real-time Sensor Data Stream Repository: TEO website
Student Training :
The students have been trained in the area of real time stream processing,
information integration, and visualization. In the area of geo-stream
processing, specifically, students have been trained in streaming data
abstraction, geo-stream query languages, stream optimization, real-time event
monitoring, and kinetic data structures.
We have regular weekly meetings, in which we discuss project progress and students present papers in literature and their own work. The informal and formal presentations help students to get a sense of research community. They also learn and practice scientific thinking and methods by summarizing and publishing research results. The process of literature survey, formation of creative ideas, qualitative evaluation of the ideas, and presentation of research results is re-enforced.
Together with a related NSF grant, we planned, prepared, and led activities for a Family Fun Saturday program called Tech Fest (Engineering a better tomorrow). The Tech Fest program was successfully carried out on October 24, 2009 at the Discovery Park of the University of North Texas. We had 150 participants (including parents) at Tech Fest. Additionally, Elm Fork has had two more Family Fun Science Saturdays where they brought out and used all of the Tech Fest lessons and materials. One of the events was Environmental CSI which had 200 participants and the second was Space Frontier which had 400 participants. Furthermore, Elm Fork is adding a middle school camp summer 2010 using our lessons and materials ~ the camp is a half-day week long camp entitled ECO-Tech – Engineering a Greener Tomorrow.
The TEO system we developed is a real-time Web-based environmental monitoring system for public access and community tracking.
Related funded research awards:
1. Yan Huang, Bill Buckles, Low-cost Wireless Network Camera Sensors for Data Collection and Traffic Monitoring, Texas Department of Transportation 0-6432, $136,540, 09/01/09 - 08/30/11
2. Yan Huang, Miguel Acevedo, Xinrong Li , Shengli Fu, Ruthanne Thompson: CRI:IAD: Infrastructure for Environmental Monitoring and Modeling using Large-scale Sensor Networks, NSF CNS-0709285, $245,999, 08/01/07 - 07/31/10
3. Miguel Acevedo, Yan Huang, Xinrong Li , Shengli Fu, Ruthanne Thompson, CI-TEAM Demonstration Project: Engaging Local Governments, Teachers and Students in CI for Environmental Monitoring and Modeling, NSF OCI-0636421, 10/01/06 - 09/30/09
Yan Huang, Energy Efficient Map Interpolation from Sensor Fields, Texas Advanced Research Program, $100,000, 05/06 -12/08