Journal
IEEE SYSTEMS JOURNAL
Volume 12, Issue 3, Pages 2056-2065Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2016.2593949
Keywords
Collaborative filtering; continuous objects monitoring; wireless sensor networks
Categories
Funding
- Qing Lan Project
- National Science Foundation of China [61572172]
- Fundamental Research Funds for the Central Universities [2016B10714]
- Open Fund through the Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis [PEFD2015-06]
- Educational Commission of Guangdong Province, China [2013KJCX0131]
- Guangdong High-Tech Development Fund [2013B010401035]
- 2013 Special Fund of Guangdong Higher School Talent Recruitment
Ask authors/readers for more resources
Continuous objects monitoring and tracking, which aims to detect the invasion of unauthorized materials of interest, is one of the most prominent applications in wireless sensor networks. In this paper, we propose a novel boundary recognition and tracking algorithm for continuous objects (BRTCO) to ensure the efficiency of objects contour extraction. On precondition of assuring the tracking accuracy, a collaborative filtering scheme is proposed to minimize the number of boundary nodes. Also, in the phase of data transmission, we take the advantage of clustering to ensure energy efficiency. A report node selection mechanism is designed based on the competition of cluster heads. Simulation results demonstrate that BRTCO can significantly reduce the total energy consumption, the number of boundary nodes, and the number of report nodes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available