Performance linked workflow composition for video processing an ecological inspiration
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Performance linked Workflow Composition for Video Processing – An Ecological Inspiration. Jessica Chen-Burger University of Edinburgh. An Ecological Motivation. An oil spill occurred at Lungkeng near Ken-Ting ( 墾丁龍坑生態區 )

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Performance linked Workflow Composition for Video Processing – An Ecological Inspiration

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Performance linked workflow composition for video processing an ecological inspiration

Performance linked Workflow Composition for Video Processing – An Ecological Inspiration

Jessica Chen-Burger

University of Edinburgh


Performance linked workflow composition for video processing an ecological inspiration

An Ecological Motivation

  • An oil spill occurred at Lungkeng near Ken-Ting (墾丁龍坑生態區 )

  • the head of the Environmental Protection Administration (EPA), Lin Jun-yi vowed to restore it to its former condition within 2 months.

  • But it is unclear as how this may be achieved –

  • There was no prior survey on the area - there isn’t a basis for referring to Lungkeng's original ecosystem prior the oil spill.

Source: Taiwan News, http://www.etaiwannews.com/Viewpoint/2001/02/14/982136471.htm


Performance linked workflow composition for video processing an ecological inspiration

  • In addition, if there was such research data into the area's ecology before the spill, one could have used it as a basis to seek insurance compensation !!


Performance linked workflow composition for video processing an ecological inspiration

In Response

  • In 1992, TERN (Taiwan long-term Ecological Research) project, a join effort with US NSF long-term ecological research, were formed.

  • Sponsored by Taiwanese National Science Council (NSC).

  • Wireless Sensor Nets were constructed and managed by NCHC.

  • NCHC (National Center for High-performance Computing).


Performance linked workflow composition for video processing an ecological inspiration

Source: NCHC


Performance linked workflow composition for video processing an ecological inspiration

  • Ken-Ting National Park

  • Under-water surveillance

Sensor Grid in Taiwan

福山

鴛鴦湖

關刀溪

塔塔加

南仁山

墾丁

Ken-Ting coral reef at

Third Nuclear Power Station

Adapted from Source: NCHC


Performance linked workflow composition for video processing an ecological inspiration

Objectives and Scopeof EcoGrid

  • To develop a scalable observational environment that is capable to hierarchically connect local environmental observatories into a global one via grid and web-service technologies.

  • To enable scientific and engineering applications in long term ecological Research (LTER) as well as environmental hazard mitigation.

  • To provide an end-to-end process from automatic information collection to automated analysis and documentation.

  • To provide a useful feedback loop for Ecologists.

  • Relevant Technology and solution:

    • Self-aware and adaptive workflow composition and management.


Performance linked workflow composition for video processing an ecological inspiration

Challenges

  • The vast amount of data available to us is of tremendous value.

  • However, how to process them efficiently and effectively is a big challenge:

    • One minute of video clip takes 1829 frames and 3.72 Mbytes;

    • That is 223.2 MB per minute, 5356.8 MB per day, and

    • 1.86 Terabytes per year for one operational camera;

    • Currently there are 3 under-water operational camera.


Performance linked workflow composition for video processing an ecological inspiration

  • Human Efforts:

    • Assuming one minute’s clip will need one human expert manual processing time of 15 minutes:

    • This means that for one camera and one year’s recording will cost a human expert 15 years’ efforts just to do some basic annotation work;

    • This is a hopeless situationand automation must be deployed in order to carry out these tasks efficiently and effectively.

  • In addition, relevant clips need to be related, organised, classified in a sensible structure, and so that additional properties may be further derived, however, this is again time consuming.


Challenges

Dynamic nature of collected video

Target information is variable and un-predictable

Limited expertise

Untrained Grid/workflow tool users

Challenges


Challenges1

Challenges

  • Effective and efficient workflow automation

  • Data co-relation identification, management and retrieval

  • Presentation of information

    • Rendering of images

    • annotation

    • co-relation with other information/clips


Challenges2

Challenges

  • Spectrum of quality in data

  • Lack of uniformity in data

  • Diverse user requirements


Opportunities

Opportunities

  • Rich processing opportunity

  • Long-term ecological documentary and analysis

  • Flexible practice that is incrementally improved over time

  • Semantic based annotation


A workflow design

A Workflow Design


Images from ken ting national park

Thank you for listening

Images from Ken Ting National Park


Thank you for listening

Thank you for listening

Gayathri Nadarajan, Yun-Heh Chen-Burger, James Malone. "Semantic-Based Workflow Composition for Video Processing in the Grid". The 2006 IEEE/WIC/ACM International Conference on Web Intelligence, Hong Kong, 18-22 December, 2006.


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