Chih-Ning Huang and Chia-Tai Chan / Procedia Computer Science 5 (2011) 58–6565

5.Conclusions

AmI environment have been a trend for future society, and it is an electronic environment that can monitor the situation around the persons or objects and give an adequate response for their needs. Accurate location information is important for location-based service. The proposed system named ZigBEACON system uses the real time RSSI to calculate the mobile node’s position. The system is not only deployed easily but also improves the accuracy of indoor location system in the AmI environment.

In this paper, the proposed ZigBEACON approach alleviates the influence of dynamic indoor environment that can effectively calculate the mobile node’s location in real time. The approach not only improves the accuracy, but also provides less calculation complexity than other improvement methods of LANDMARC. Comparing the results with that of Z-LANDMARC, the proposed methodology reduces about 0.28 to 1.57m estimation error distance and has 29% improvement on average error distance. The ZigBEACON approach is an adequate solution to the indoor location system for AmI applications.

Reference

[1] Emile Aarts, Reiner Wichert. Ambient intelligence. In: Hans-Jörg Bullinger (ed) Technology Guide Principles – Applications – Trends.

Springer; 2009, pp 244-249

[2] Schilit B, Adams N, Want R. Context-aware computing applications. Proceedings Workshop on Mobile Computing Systems and Applications;

1994, pp 85-90

[3] Huang CN, Chiang CY, Chang JS, Chou YC, Hong YX, Hsu SJ et al. Location-aware fall detection system for medical care quality

improvement. Proceedings of the 3rd International Conference on Multimedia and Ubiquitous Engineering; 2009, pp 477-480

[4] Liu H; Darabi H; Banerjee P; Liu J. Survey of wireless indoor positioning techniques and systems, IEEE Transactions on Systems, Man, and

Cybernetics, Part C: Applications and Reviews; 2007, 37(6):1067-1080

[5] Ni LM, Liu YH, Lau YC, Patil AP. LANDMARC: indoor location sensing using active RFID, In: Proceedings of the 1st IEEE International

Conference on Pervasive Computing and Communications; 2003, pp 407-415

[6] Zhang T, Chen ZY, Ouyang YN, Hao JY, and Xiong Z. An improved RFID-based locating algorithm by eliminating diversity of active tags

for indoor environment. The Computer Journal; 2008, 52(8): 902-909

[7] Chen WH, Chang HH, Lin TH, Chen PC, Chen LK, Hwang SJ et al. Dynamic indoor localization based on active RFID for healthcare

applications: a shape constraint approach, In: Proceeding of the 2nd International Conference on Biomedical Engineering and Informatics;2009, pp 1-5

[8] Jiang XJ, Liu Y, Wang XL. An enhanced approach of indoor location sensing using active RFID, In: Proceeding of the WASE International

Conference on Information Engineering; 2009, pp 169-172

[9] Hsu PW, Lin TH, Chang HH, Chen YT, Tseng YJ, Hsiao CH et al. Simulations and experiments for optimal deployment of an RFID-based

location-aware system, Wirel Commun Mob Comput; 2009, doi: 10.1002

[10] Jain S, Sabharwal A, Chandra S. An improvised localization scheme using active RFID for accurate tracking in smart homes, In: Proceeding

of the 12th International Conference on Computer Modelling and Simulation; 2010, pp 51-56

[11] Chen X, Wang ZJ. Reliable indoor location sensing technuque using active RFID, In: Proceeding of the 2nd International Conference on

Industrial Mechatronics and Automation; 2010, pp 160-163

[12] Maciej M, Karol B, Lukasz K, Krzystof N. Pattern matching localization in ZigBee wireless sensor networks, In: Proceeding of the 18th

International Conference on Microwave Radar and Wireless Communications; 2010, pp 1-4

[13] UBEC Corp.(2005) UZ2400 Data sheet (RF + Baseband + Mac) DS 2400-2, pp:79

[14] Andersen JB, Rappaport TS, Yoshida, S. Propagation measurements and models for wireless communications channels, IEEE

Communications Magazine; Jan, 1995, 33(1): 42-49