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Chih-Ning Huang and Chia-Tai Chan / Procedia Computer Science 5 (2011) 58–65

4.2.The results of ZigBEACON system

The ZigBEACON system is based on the k-nearest neighbor algorithm which is adopted by the famous RFID-based LANDMARC system. To evaluate the ZigBEACON approach, we compare the results of ZigBEACON system with that of ZigBee-based LANDMARC system, called Z-LANDMARC latter, that accomplishes LANDMARC approach by SuperNode. Based on the result on optimal number of nearest reference node(s), we will show the comparisons at the p = 4 condition.

4.2.1.The comparison of Euclidean distance distribution

The Euclidean distance between the mobile node and the reference node i calculated by Equation (2) means the similarity of RSSI between the mobile node and the reference node i. The smaller Ei is, the nearer the reference node i is. If the p-nearest reference nodes are gathered together around the mobile node, the accuracy will be improved. Figure 5 and Figure 6 are the Euclidean distance distribution of Z-LANDMARC approach and ZigBEACON approach. The subtitles, (a), (b), (c) and (d) of these two figures are the results when the mobile node at position A, B, C and D individually as shown in Figure 3. Comparing Figure 5 with Figure 6, we can easily discover that the Euclidean distance distributions of ZigBEACON approach are smoother than that of Z-LANDMARC approach. Unlike the results of Z-LANDMARC approach that have multi-hollow distribution, the results of our proposed approach only have a main hollow. So the ZigBEACON approach can effectively choose the p-nearest reference nodes around the mobile node. For example, Figure 5 (a) has three hollows at (2.5, 0.875), (4.5, 4.875) and (8.5, 0.875), especially (8.5, 0.875) is far from the mobile node’s position, A (1.5, 1.875), that will increase the error distance, but Figure 6 (a) only have two hollows, (2.5, 0.875) and (4.5, 4.875).

Fig. 5. The Euclidean distance distribution of Z-LANMARC approach when mobile node is at (a) A (1.5, 1.875); (b) B (3.5, 1.875); (c) C (5.5,

1.875); (d) D (7.5, 1.875).

Fig. 6. The Euclidean distance distribution of ZigBEACON approach when mobile node is at (a) A (1.5, 1.875); (b) B (3.5, 1.875); (c) C (5.5,

1.875); (d) D (7.5, 1.875).

4.2.2.The comparison of error distance

Comparing the results with that of Z-LANDMARC approach, ZigBEACON approach reduces 0.47m that is about 29% improvement on average error distance. The average error distance is 1.15 0.54m for ZigBEACON and

1.62 0.9m for Z-LANDMARC, the maximum error distance is 1.64m for ZigBEACON and 2.99m for Z-LANDMARC, and the minimum error distance is 0.24m for ZigBEACON and 0.52m for Z-LANDMARC. In short,

theZigBEACON approach can improve the accuracy of indoor location significantly.