Intelligent Resource Selection For Sensor-Task Assignment: A Knowledge Based Approach

Geeth Ranmal De Mel, Wamberto Weber Vasconcelos, Timothy J Norman

Research output: Contribution to conferenceOtherpeer-review

Abstract

Sensing resources play a crucial role in the success of critical tasks such as surveillance. Therefore, it is important to assigning appropriate sensing resources to tasks such that the selected resources fully cater the needs of the tasks. However, selecting the right resources to tasks is a computationally hard problem to solve. Most of the existing approaches address the efficiency aspect of the resource selection by considering the physical aspects of the sensor network (e.g., range, power, etc.) but have ignored important domain related properties such as capabilities of assets, environmental conditions, policies and so on which makes the selection effective. In this paper we present a knowledge rich mechanism to intelligently select resources for tasks such that the selected resources sufficiently cover the needs of the tasks. Ontologies are used to capture the crucial domain knowledge and semantic matchmaking is used to perform sensor-task matching. A combination of ontological and first-order-logic reasoning is considered for the solution architecture.
Original languageEnglish
Number of pages7
Publication statusPublished - Nov 2010
EventInternational Conference on Advanced Topics in Artificial Intelligence - Phuket, Thailand
Duration: 29 Nov 201030 Nov 2010

Conference

ConferenceInternational Conference on Advanced Topics in Artificial Intelligence
Country/TerritoryThailand
CityPhuket
Period29/11/1030/11/10

Bibliographical note

This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence and was accomplished under Agreement Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies,either expressed or implied, of the U.S. Army Research Laboratory,the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.

Keywords

  • sensors
  • platforms
  • knowledge representation
  • reasoning
  • semantic matchmaking
  • resource assignment

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