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EBCO - Efficient Boundary Detection and Tracking Continuous Objects in WSNs

  • Chauhdary, Sajjad Hussain (Department of Computer Science and Engineering Korea University) ;
  • Lee, Jeongjoon (Convergence Technology R&D Center LS Industrial Systems Co., LTD.) ;
  • Shah, Sayed Chhattan (Vehicle and Defense IT Convergence Research Division(ETRI) Electronics and Telecommunications Research Institute) ;
  • Park, Myong-Soon (Department of Computer Science and Engineering Korea University)
  • Received : 2012.05.29
  • Accepted : 2012.10.08
  • Published : 2012.11.30

Abstract

Recent research in MEMS (Micro-Electro-Mechanical Systems) and wireless communication has enabled tracking of continuous objects, including fires, nuclear explosions and bio-chemical material diffusions. This paper proposes an energy-efficient scheme that detects and tracks different dynamic shapes of a continuous object (i.e., the inner and outer boundaries of a continuous object). EBCO (Efficient Boundary detection and tracking of Continuous Objects in WSNs) exploits the sensing capabilities of sensor nodes by automatically adjusting the sensing range to be either a boundary sensor node or not, instead of communicating to its neighboring sensor nodes because radio communication consumes more energy than adjusting the sensing range. The proposed scheme not only increases the tracking accuracy by choosing the bordering boundary sensor nodes on the phenomenon edge, but it also minimizes the power consumption by having little communication among sensor nodes. The simulation result shows that our proposed scheme minimizes the energy consumption and achieves more precise tracking results than existing approaches.

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  2. Toxic gas boundary area detection in large-scale petrochemical plants with industrial wireless sensor networks vol.54, pp.10, 2016, https://doi.org/10.1109/mcom.2016.7588225
  3. Energy Efficient and Accurate Monitoring of Large-Scale Diffusive Objects in Internet of Things vol.21, pp.3, 2012, https://doi.org/10.1109/lcomm.2016.2634526