1. Xiaofan Jiang, Chieh-Jan Mike Liang, Kaifei Chen, Ben Zhang, Jeff Hsu Jie Liu, Bin Cao, and Feng Zhao Microsoft Research Asia 20120730-Neight

2.   MOTIVATION  PROXIMITY ZONE  Empirical Definition  EVALUATION OF EXISTING TECHNOLOGIES  LIVESYNERGY PLATFORM  EVALUATION OF LIVESYNERGY  APPLICATION DEPLOYMENT  CONCLUSIONS Outline

3.   To make applications intuitive to human users, the discovered objects in the environment must be within the personal interaction sphere Computer automatically wake up Refrigerator change its user interface  Many typical low power communication technologies, (Bluetooth, ZigBee) have difficulties maintaining robust communication zones Motivation

4.   propose methodologies and systematically compare the proximity zones created by various wireless technologies(BLE, ZigBee, and RFID reader)  Design, Implement, and Evaluate a magnetic- induction based wireless proximity sensing platform  Deploying LiveSynergy in an real-world application Contributions

5.   Boundary sharpness: boundary of proximity zone should be binary  Boundary consistency: detection should be consistent over time PROXIMITY ZONE

6.   Obstacle penetration: Beaconing node and listening node can be mobile and against obstructions  Additional metrics: 1. Range and geometric shape of zones 2. Beaconing frequency achievable 3. Power consumption 4. Form-Factor of the mobile tag 5. Cost of overall system PROXIMITY ZONE

7.  Classification of Points

8.  Classification of Zones

9.  Three proximity zones

10.  Questions? Proximity Zones

11.   Use support vector machines (SVM) as the classifier seeks maximum-margin hyperplane to separate two classes  w and b are the parameters to define the hyperplane to separate the two classes. Classifier

12.   Two user-definable parameters: Error tolerance: - Smooth boundary vs. non-smooth boundary -Tradeoff between training loss and regularization -Cost parameter C Strictness: -Expect the white zone and the black zone contain no grey points -Related to error tolerance but non-symmetry Classifier

13.  Cost parameter C: the cost of false positive C’: the cost of false negative C’ Strictness parameter: Classifier

14.  Kernel Trick

15.   Size: Size of the white and grey zone, which can be computed numerically based on the boundaries.  Boundary sharpness:  Fitness: How well the zone boundaries fit the data, or a confidence measure of the proximity zone classification. Matrix

16.  Questions? Classifier

17.   Hardware setup: TI CC2540 BLE dev boards (transmitting on 2.4 GHz at 0 dBm), A pair of TelosB motes with 802.15.4-compliant TI CC24240 radio(transmitting on 2.4 GHz at 0 dBm) A Impinj Speedway R1000 RFID reader (transmitting on 902 MHz at 8 dBm) Boundary Sharpness and Consistency

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20.  Human Obstacle Penetration

21.   Signal propagation and geometry: RFID antennas usually have a radiation angle less than 180 degrees  Form Factor and Costs: RFID can produce a more consistent and smaller grey zone 802.15.4 and BLE have advantages in both form factor and costs. Additional Metrics

22.  Questions? Evaluation

23.   Pulse Transmitter: (use AC power) Four primary hardware microcontroller (MCU) and radio magnetic transmitter tuned at 125kHz Energy metering mechanical relay for actuation. LIVESYNERGY PLATFORM

24.   Link Receiver: ( battery-powered) Three primary hardware 9.2cm ×5.8cm × 2.3cm enclosure MCU and radio 3D magnetic coil wake up chip LIVESYNERGY PLATFORM

25.  Boundary Sharpness and Consistency

26.   human body has very little impact on the MI signal propagation Body orientation vs. distance

27.   Geometry: two dimensions extends to all directions, covering 360◦  Range: maximum range (i.e., radius) is around 5m Additional Metrics

28.  APPLICATION DEPLOYMENT Diners enter the cafeteria from the entrance at the lower left corner at different times

29.   Each diner takes a different route and visits various food counters on the way  Recorded a video as the customers walk around the cafeteria purchasing food. - Use video timestamps Experment

30.  Result

31.   Values: 1.Propose methodologies and systematically compare the proximity zones 2.Deploying LiveSynergy in an real-world application  Future? 1.MI still can implement in mobile phone… Summary