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Indoor Localization

Using a Modern Smartphone. Indoor Localization. Carick Wienke Advisor: Dr. Nicholas Kirsch University of New Hampshire ECE 791H. Problem Description. A firefighter is trying to navigate through a burning building but the route is blocked and he needs to find another…

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Indoor Localization

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  1. Using a Modern Smartphone Indoor Localization Carick Wienke Advisor: Dr. Nicholas Kirsch University of New Hampshire ECE 791H

  2. Problem Description A firefighter is trying to navigate through a burning building but the route is blocked and he needs to find another… • System for precise indoor localization • Other applications as well • Find a route or determine your position inside an unknown building • Current systems do not work efficiently • GPS fails without line of sight to the sky • WLAN Trilateration is not precise enough for most applications

  3. Possible Solutions • No Infrastructure • Can be implemented in any building • Greater error than other systems • New Infrastructure • Can be designed and installed to provide precise localization • System only works in certain buildings • High cost, especially in larger buildings

  4. Possible Solutions (cont.) • Common Infrastructure • Builds upon the infrastructure that is commonly found in buildings, e.g. Wireless LAN Access Points (APs) • Can be applied to most buildings • Only cost due to the receiver • Error will not increase over time • Infrastructure is not designed for localization, leading to a less precise position estimation

  5. Our Solution • Compliment WLAN trilateration with direction of movement • Modern Smartphone for measuring, calculating, and displaying information • WLAN Connectivity • Accelerometer • Compass / Magnetic Sensor • Dell Streak

  6. WLAN Trilateration • Inputs • Location of the APs • Received signal strength(RSS) from each of the AP • Output • An area of probable location • Selecting a single point

  7. Direction of Movement • Input • Orientation of device relative to the ground • Provided by Android API • Direction of movement relative to the phone • 3 accelerometers provide data relative to the device • Assuming the device is parallel to the ground reduces the complexity, using only 2 accelerometers • Orientation of phone relative to the building • Compass • Output • Velocity vector

  8. Synthesis WLAN Trilateration and Direction of Movement • Comparing the direction of movement with the geometry of the floor plan can decrease the estimated area. • If the device is moving right, it is reasonable to assume that is moving toward the hallway and not the wall. • Maximum Likelihood Function

  9. Budget Dell Streak $550 Image from Dell Streak product webpage

  10. Project Timeline

  11. Basic Application Phase 1: 1 – 2 weeks • Become familiar with programming, compiling, and loading applications for the Streak • Create a “Hello World!” application which will simply display text on the device. • Extend to display the WLAN RSS for all the APs within range

  12. Display Map Phase 2: 5 – 8 weeks • Storing a digital map on the devicethat allows • To draw to screen easily • To check for collisions between the path and walls • State Machine

  13. Display Map (cont.) Phase 2: 5 – 8 weeks • Ability to zoom, translate, and rotate the map on the screen • Complexity can be reduced by using constant zoom and rotation • Testing • Does it display properly? • Hardcode different zooms, translations, and rotations. Do they display properly?

  14. WLAN Trilateration Phase 3: 8 – 10 weeks • Calculates a probable range of distance that the device is from each AP • Create an algorithm to approximate location based on these distances • Testing • Check approximate location under a number of circumstances • Stationary vs. moving • Different locations, rooms • How is the response time? Does it occur in real time?

  15. Accelerometer and Compass Phase 4: 2 – 3 weeks • Data Mining • Store/Print information about the readings from the sensors • Compare human movements like walking, running, turning, etc. to the sensor reading

  16. Compute Direction of Movement Phase 5: 3 – 4 weeks • Create an algorithm to determine how the person is moving from the sensor readings • Draw an arrow/symbol on the screen • Testing • Move around in various ways • Compare computed movements to actual movements made • How is the response time? Does it occur in real time?

  17. Synthesize Information Phase 6: 6 – 8 weeks • Calculate a location from both trilateration and movement information • Determine WLAN trilateration heat map • Reduce map based direction of movement • How heavily are the two parts weighed to calculate the one point? • Testing • Same as Phase 3: WLAN Trilateration

  18. Compare Methods Phase 7: 2 – 3 weeks • Gather enough data to compare the precision and accuracy of the two methods • How does including direction of movement improve localization? Is error reduced? • How does the system perform compared to other systems that have been created? • What other information provided by the device can be incorporated into the algorithm?

  19. Questions?

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