A data aggregation scheme for boundary detection and tracking of continuous objects in WSN

Hyun Jung Lee, Myat Thida Soe, Sajjad Hussain Chauhdary, Soyeon Rhee, Myong Soon Park

Research output: Contribution to journalArticle

6 Citations (Scopus)


Efficient and accurate detection and tracking of continuous objects such as fire and hazardous bio-chemical material diffusion requires an extensive communication between nodes in wireless sensor networks. In this paper, we propose an efficient algorithm that monitors a moving object by selecting a subset of monitoring data of object boundary nodes. The proposed algorithm uses a Data Aggregation method to reduce the number of report messages and a piecewise Quadratic Polynomial Interpolation algorithm to find the boundary points precisely. Simulation results show that the proposed scheme significantly reduces the number of report messages to the sink node and also improves boundary accuracy.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIntelligent Automation and Soft Computing
Publication statusAccepted/In press - 2016 May 25



  • continuous object tracking
  • data aggregation
  • Wireless sensor network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics

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