Indoor Location System based on 802.15.4

1. Indoor Location System based on 802.15.4 9112636戴毓廷 9112029吳信賢 9112029許碩仁

2. Outline • Introduction • Methodology • Simulation • Hardware equipment • Related work • Reference

3. Introduction • “Sensing data without location is meaningless.” [2] • Using Global Position System (GPS) for every sensor is expensive. • Local Position System (LPS): using Received signal strength (RSS) or time of arrival (TOA) to get location information

4. Introduction • Combining GPS and LPS can give a low cost location system. • In this project, we would like to implementation a fine indoor location estimation based on RSS.

5. Methodology • Reference Devices (RD) Measuring BD’s RSS value, and push RSSI value to coordinator. RD have clear information of their position. • Blindfolded devices (BD) Broadcast a packet so RD can get RSSI value. BD do not know where he is.

6. Methodology • Coordinator Collecting the RSSI values form every RD, and then push them to server. • Server Running a program that can get value from COM port, getting RSSI values and performing location algorithm.

7. Router / Reference Reference PAN coordinator PC Blindfolded Wireless link Physical wire Blindfolded Reference Reference Methodology

8. Methodology • Location algorithm: 1. RSSI and power relationship. 2. Power and distance relationship. 3. Distance and location relationship.

9. Methodology 1. RSSI and power relationship: By experimental measuring. 2. Power and distance relationship: [1]

10. Methodology • Here we choose [1]

11. Methodology 3. Distance and location relationship: Here we use a method called Geometry method. The Geometry Location Algorithm has some different types: • Gravity of Area Apexes Method. • Line of Position Method. • Section of Area Method. • Weighted Area Apexes Method.

12. Methodology Gravity of Area Apexes Method: Step1: Plotting Cycles. Center: The three positions of reference devices. Radius: The measured distance between RD and BD. Step2: Find the six intersection points. RD RD RD

13. BD Methodology Step3: Find the “meaningful” intersection points. Step4: So far, we have three “meaningful” intersection points. Calculate the gravity of the three points and the position of gravity is our location estimation result.

14. Simulation • Consider a right triangular area with three RD which locate at (0,0), (0,10), (5, ) and a single BD locates at some unknown position. • We random choose the position of BD, and add some random noise on the actual distances between the three RDs.

15. Simulation Assume the measurement error of RSS is between -5% and +5% B.D. @ (1,1) Estimation result: (1.1127, 0.7729) B.D. @ (5,5) Estimation result: (4.8548,5.0718)

16. Hardware equipment • UZ2400 RF chip, UBEC, Taiwan. • 8051 platform.

17. Related work • Create a program to handle RSSI and location estimation on server. • A filter or some solution to deal with RSSI jumping when BD stay at the same position. • Channel access problem.

18. Related work • We plan to complete one dimension first, and than using the algorithm discussed above to challenge two dimension.

19. Reference [1] Neal Patwari, Alfred O. Hero, Matt Perkins, Neiyer S. Correal, Robert J. O’Dea,“Relative Location Estimation in Wireless Sensor Networks”IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 8, AUGUST 2003 [2]J. M. Rabaey, M. J. Ammer, J. L. da Silva, Jr., D. Patel, and S. Roundy, “Picorodio supports ad hoc ultra-low power wireless networking,”IEEE Comput., vol. 33, pp. 42–48, July 2000.

20. Thank you !!