Weighted distance-based m/n track initiation methods for wireless sensor networks in clutter
Proceedings of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Probabilistic inference of object identifications for event stream analytics
Proceedings of the 16th International Conference on Extending Database Technology
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The aim of this paper is to develop a distributed Multi-Target Tracking (MTT) algorithm over wireless sensor networks which has the ability of online implementation in low-cost sensor nodes due to its lower computational complexity and execution time compared to the other MTT systems. The Monte Carlo (MC) implementation of JPDAF (MC-JPDAF) is applied to the classical problem of TT in a cluttered area. Also, to make the tracking algorithm scalable and usable for large networks, the distributed Expectation Maximization (EM) algorithm is used via the average consensus filter in order to diffuse the nodes’ information over the whole network. Furthermore, some simplifications and modifications are made to MC-JPDAF algorithm in order to reduce the computation complexity of the tracking system and make it suitable for low-energy sensor networks. Finally, the simulations of tracking tasks for the proposed system are given.