Modeling of Location Estimation for Object Tracking in WSN

Abstract

Location estimation for object tracking is one of the important topics in the research of wireless sensor networks (WSNs). Recently, many location estimation or position schemes in WSN have been proposed. In this paper, we will propose the procedure and modeling of location estimation for object tracking in WSN. The designed modeling is a simple scheme without complex processing. We will use Matlab to conduct the simulation and numerical analyses to find the optimal modeling variables. The analyses with different variables will include object moving model, sensing radius, model weighting value , and power-level increasing ratio k of neighboring sensor nodes. For practical consideration, we will also carry out the shadowing model for analysis.

Pattern Recognition of Human Postures Using the Data Density Functional Method

“…Additionally, several methods of rehabilitation based on statistical learnings have also fulfilled fruitful performances for the recovery of human activities damaged by injury or known diseases, such as heart failure [7], stroke [8][9][10][11], Parkinson's disease [12] and osteoporosis [13]. Among these applications, the hardware schemes of data acquirement commonly utilized wireless sensors [14][15][16][17], personal portable devices [9, 16,18], robotic assistance [19][20][21][22], or other commercial equipment [1,23,24]. The acquired results were then fed into relevant image-or video-based techniques [10][11][12]17,21,25,26] for further human posture recognitions.…”