Adaptive Accurate Indoor-Localization Using Passive RFID Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology Nanjing University, China Presenter: Dr. Lei Xie, Associate Professor

Adaptive Accurate Indoor-Localization Using Passive RFID Outline Motivation & Observation 1 Our Solution 3 Localization Model 2 Performance Evaluation 4 Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Library Management Warehouse Management Adaptive Accurate Indoor-Localization Using Passive RFID Scenario Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Observation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Observation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China More unstable than other wireless devices

Adaptive Accurate Indoor-Localization Using Passive RFID Observation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China NOT monotonically decreasing with the increasing distance

Adaptive Accurate Indoor-Localization Using Passive RFID Observation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China CAN NOT be detected Increasing rapidly with increased power arrived in its saturation value

Adaptive Accurate Indoor-Localization Using Passive RFID Motivation The traditional methods, like LANDMARC-based methods, are not suitable for adaptive indoor-localization using passive RFID technology: Multi-path effect and noise in the realistic indoor-environment; Unstable RSSI value and special reading phenomenon of passive tag. Challenges The RSSI value is not linearly increasing while the reader’s power increases. The RSSI value of passive RFID tag is more unstable than the active tag. Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID RSSI can’t be detected RSSI increases sharply with large standard deviation RSSI converges to a saturated value with small standard deviation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Localization Model and Scenario

Adaptive Accurate Indoor-Localization Using Passive RFID Localization Model and Scenario Localization areas like shelf in library, supermarket Accuracy: the average error should be less than a certain threshold, e.g. 50cm; Time-delay: the time duration for localization should be less than a certain threshold, e.g. 5 seconds in realistic application. Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID System framework Calibrate the unstable reading of tags by using auto-feedback data Measuring tags in the stable region by using appropriate power Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping ---- Motivation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Antenna : Target tag : Reference tag Too small power Too large power Appropriate power Can not be detected Interference from the reference tag far away. Only the target tag and the reference tags close to target tag can be activated

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping Different reading results between maximum power and smaller power Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping Finding the appropriate power for the target tag Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping If the RSSI equals to 0, it then cannot effectively discriminate the nearby tags from the distant tags in regard to distance Filter the reference tags when it can not be detected by enough number of antennas

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping Filtering the reference tags by comparing the activating power Power 1Power 2Power 3Power 4 Target tagp1p2p3p4 Reference 1p’1p’2p’3p’4 |p1-p’1||p2-p’2||p3-p’3||p4-p’4| (25.7, 18.7, 30.7, 29.7)(28.7, 29.7, 24.7, 22.7) Reference tagTarget tag (3, 11, 6, 7) If the threshold is 5, Then Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China For example:

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Power Stepping Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Adaptive When the number of reference tags are too small to support localization

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Grid-based Calibration ---- Motivation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Auto-detection technologies can have feedbacks for result The right grid with exact position, detected by feedbacks. Leverage these data for the following localization

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Grid-based Calibration Rule Checking —— Generation For each grid, we can have a rule set L {l i } S1-S2S1-S3S1-S4S2-S3S2-S4S3-S4 (3000, 1500, 1000, 500) (3100, 1400, 980, 450) For one certain grid: … … S 1 – S 2 S 1 – S 2 >1500 as one rule for the grid. Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Adaptive Grid-based Calibration Rule Checking —— Checking Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Integrated Method Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China More feedback fingerprints can provide higher success ratio

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Both methods have much better performance than the baseline method APS method can effectively reduce the minimum error AGC method can use the automatic feedback fingerprints to calibrate negative impact

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Maximum error in APS method is much larger than AGC method Minimum error in APS method is smaller than AGC method.

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China average error is smaller by more number of reference tags Maximum error by 10 reference tags is smaller than it by 15 reference tags More interference existed by more reference tags

Adaptive Accurate Indoor-Localization Using Passive RFID Evaluation Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China Time-delay of grid-based calibration procedure is fairly small. The APS method and Integrated method have an average delay of 2.5 seconds. It is caused by the power stepping to find the appropriate transmitting power.

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