Presentation on theme: "CSI 5169 --- Wireless Networks and Mobile Computing Indoor Localization Zhang"— Presentation transcript:
CSI Wireless Networks and Mobile Computing Indoor Localization Zhang
Outline Introduction –Definition –Important parameters Indoor Localization Methods –Proximity Detection –Triangulation –Scene Analysis Indoor Localization Systems –Proximity Based –RF Based –Cameras Based Comparison of Common Indoor Localization Systems
Introduction - Defination Def. Wirelessly locate objects or people inside a building in real time. Indoor Positioning Systems (IPS) Real-time Locating Systems (RTLS)
Introduction - Important Parameters Accuracy Coverage Availability Update Rate Line of Sight (LoS) and Non Line of Sight (NLoS) Costs and System Complexity
Introduction - LoS / NLoS Line of Sight (LoS) and Non Line of Sight (NLoS)
Indoor Localization Methods/ Algorithm Methods/Algorithm Proximity / CoOTriangulation Direction based Angle based Distance based Time based Signal Property based Scene Analysis
Proximity Detection: Sensors detect and measure reflected Infrared or visiable light or RF wave to detect the presence of an object or person in certain areas. Highest Received Signal Strength = Highest Probability Methods / Algorithm - Proximity / Cell of Origan
Advantages No complicated algorithms Easy to implement Low cost Disadvantages Low accuracy - room level Identification problem Methods / Algorithm - Proximity / Cell of Origan
ToA: Time of Arrival The precise measurement of the arrival time of a signal transmitted from a mobile device to several receiving sensors. The distance between the mobile device and each receiving sensor can be determined. Methods / Algorithm - Time based
Advantages High Accuracy 2D / 3D Disadvantages Precise time synchronization (1 micro-second, 300m error) Solutions are typically challenged in environments where a large amount of multipath or interference may exist. Methods / Algorithm - Time based - ToA
TDoA: Time Difference of Arrival Using relative Arrival time measurements at each receiving sensor The synchronization between tag and each sensor is not necessary Example: T XC - T XA = s TDoA C_A T XB - T XA = s TDoA B_A Methods / Algorithm - Time based - TDoA
AoA/DoA: Angle of Arrival / Direction of Arrival (DoA) Determining the angle of incidence at which signals arrive at the receiving sensor. Methods / Algorithm - Angle based - AoA
More sensors = Higher accuracy
Advantages No synchronization requirement Works well in situations with direct line of sight Disadvantages Susceptibility to multipath interference Methods / Algorithm - Angle based - AoA
Signal attenuation can be exploited for distance estimation. Methods / Algorithm - Signal Property Based
RSS: Based on the attenuation model, the Received Signal Strength can be used to estimate the distanced of a person or a mobile object. P R : Received signal strength at the receiver P T : Transmitted power strength at the emitter G T G R : Antenna gains of transmitter and receiver d: Distance P: The path loss factor Methods / Algorithm - Signal Property Based
The path loss factor (P) is related to the environmental conditions P = 2 for free space P > 2 for environments with NLoS multipath P ≈ (4 - 6) for typical indoor environments In real world application, interference, multipath propagation and presence of obstacles and people leads to a complex spatial distribution of RSS. RSS Indicator (RSSI): averaged P R over a certain sampling period Methods / Algorithm - Signal Property Based
M(-35, -50, -48, -60, -58,-24) vs. Database Methods / Algorithm - F ingerprinting
Advantages High accuracy NLoS Disadvantages Complicated algorithms Not easy to implement High cost Methods / Algorithm - F ingerprinting
Indoor Localization Systems
WIFI: (a superset of IEEE standard) can be used to estimate the location of a mobile device within this network. Indoor Localization Systems - WIFI WIFI Range50-100m Accuracy1m Method RSSI Fingerprinting, TDoA NLOS/LOSNLOS Application Office Space, Person, Objects
RFID (Radio Frequency IDentification) system consists of readers with antennas which interrogates nearby active transceivers or passive tags. Indoor Localization Systems - RFID RFIDActivePassive Range10-100m1-5m Accuracy1m0.2m Method RSSI Fingerprinting, TDoA AoA, TDoA NLOS/LOSNLOSLOS ApplicationMoving ObjectsAssembly Industry
ZigBee is a wireless technology particularly designed for applications which demand low power consumption and low data transmission. Indoor Localization Systems - ZigBee ZigBee Range20-30m Accuracy2m MethodRSSI NLOS/LOSNLOS Application Warehouse management
SystemsAccuracyCoverageMethodsNLoS/Los Power Consume CostRemarks GPS10-50m Poor Indoor ToANLoSHigh Unstable Proximity3-5m Room level ProximityLoSLow ID? Cameras Networks 0.5m Building level Scene AnalysisLoSLowHighID? WIFI1m Building level RSSI Fingerprinting /TDoA NLoSHigh WIFI Covered RFID (Active) 1m Building level RSSI Fingerprinting NLoSMed Long Distance RFID (Passive) 0.2m Room level TDoA/ AoALoSLow No Data Exchange Bluetooth1-2m Building level RSSI Fingerprinting NLoSLowMed High Data Rate ZigBee2m Building level RSSI Fingerprinting NLoSLow Low Data Rate
References  Z. Farid, R. Nordin, and M. Ismail, "Recent Advances in Wireless Indoor Localization Techniques and Systems," Journal of Computer Networks and Communications, vol. 2013,  R. Mautz, "Indoor positioning technologies," Habilitation Thesis, Department of Civil, Environmental and Geomatic Engineering, Institute of Geodesy and Photogrammetry, Habil. ETH Zürich, Zurich,  H. Koyuncu and S. H. Yang, "A survey of indoor positioning and object locating systems," IJCSNS International Journal of Computer Science and Network Security, vol. 10, pp ,  A. Aboodi andW. Tat-Chee, “Evaluation ofWiFi-based indoor (WBI) positioning algorithm,” in Proceedings of the 3rd FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing (MUSIC ’12), pp. 260–264, June  S. Chan and G. Sohn, ¡°Indoor localization using Wi-Fi based fingerprinting and trilateration techiques for LBS applications,¡± in Proceedings of the 7th International Conference on 3D Geoinformation, Quebec, Canada, May 2012.
Question 1 The RSSI pattern is shown below. 3 Wifi routers 9 refernces points Q: Where is M(1.2, 2.6, 4.5) in this pattern?
Question 1 Q: Where is M(1.2, 2.6, 4.5) in this pattern? A: Measured RSSI of Wifi one is 1.2. Red zone (referenced RSSI of Wifi one is 1) are possible locations
Question Q: Where is M(1.2, 2.6, 4.5) in this pattern? A: Measured RSSI of Wifi two is 2.6. Green zone (referenced RSSI of Wifi two is 3) are possible locations.
Question Q: Where is M(1.2, 2.6, 4.5) in this pattern? A: Measured RSSI of Wifi three is 4.5. Blue zone (referenced RSSI of Wifi two is 5) are possible locations. The intersection of three zones is the location of M.
Question 2 The RSSI pattern is shown above. 3 Wifi routers 9 refernces points Q: Where is M(5, 2, 1) in this pattern? Is there any methods to increase the acceracy by optimizeing the system?
Question 2 Q: Is there any methods to increase the acceracy of this system? A: More Wifi routers, more reference points
Question 3 A company with 3 buildings. Building A: Working Office (Wifi coverd) Building B: Assembly lines Building C: Warehouse Q: Building A: Locating persons + high rate data transmission Building B: Accurate positioning products + no data transmission Building C: Locating forklifts + low rate data transmission Which indoor localization system will you choose for Building A, Building B, Building C, respectively? why?
Question 3 A company with 3 buildings. Building A: Working Office (Wifi coverd) Building B: Assembly lines Building C: Warehouse Q: Building A: Locating persons + high rate data transmission Building B: Accurate positioning products + no data transmission Building C: Locating forklifts + low rate data transmission Which indoor localization system will you choose for Building A, Building B, Building C, respectively? why? Answers: A: WIFI. Wife covered, high data rate, mobile phone. B: RFID(Passive). Small tag size, high acceracy, low cost. C: ZigBee. Low power consumption, low cost, low data rate