Accuracy Characterization of Cell Tower Localization

Slides:



Advertisements
Similar presentations
DAISY DAISY Data Analysis and Information SecuritY Lab Detecting Driver Phone Use Leveraging Car Speakers Presenter: Yingying Chen Jie Yang, Simon Sidhom,
Advertisements

January 6. January 7 January 8 January 9 January 10.
Characteristics of public quick chargers to support EV users
CILoS: A CDMA Indoor Localization System Waqas ur Rehman, Eyal de Lara, Stefan Saroiu.
Keweenaw North Waterway Buoy Bob Shuchman: Colin Brooks: Nate Jessee:
Verizon Proposed Cell Phone Tower in Grandview Cemetery Glendale Residents Oppose Grandview Cemetery Cell Tower because: It will detract from the beauty.
Accuracy Characterization for Metropolitan-scale Wi-Fi Localization Yu-Chung Cheng (UCSD, Intel Research) Yatin Chawathe (Intel Research) Anthony LaMarca.
ACCURACY CHARACTERIZATION FOR METROPOLITAN-SCALE WI-FI LOCALIZATION Presented by Jack Li March 5, 2009.
Accuracy Characterization for Metropolitan-scale Wi-Fi Localization Ying Wang, Xia Li Ying Wang, Xia Li.
P-1. P-2 Outline  Principles of cellular geo-location  Why Geo-Location?  Radio location principles  Urban area challenges  HAWK – suggested solution.
Tracking Fine-grain Vehicular Speed Variations by Warping Mobile Phone Signal Strengths Presented by Tam Vu Gayathri Chandrasekaran*, Tam Vu*, Alexander.
Final Year Project LYU0301 Location-Based Services Using GSM Cell Information over Symbian OS Mok Ming Fai CEG Lee Kwok Chau CEG
PeopleTones: a system for the detection and notification of buddy proximity on mobile phones Kevin A. Li Timothy Sohn Steven Huang William G. Griswold.
D ETECTING D RIVER P HONE U SE L EVERAGING C AR S PEAKERS Jie Yang, Simon Sidhom, Gayathri Chandrasekaran, Tam Vu, Hongbo Liu, Nicolae Cecan, Yingying.
Urban Economics Economics generally studies how markets work A market consists of a collection of buyers and sellers exchanging goods and services Urban.
DAISY Data Analysis and Information SecuritY Lab
Review: Accuracy Characterization for Metropolitan-scale Wi-Fi Localization Authors: Cheng, Chawathe, LaMacra, Krumm 2005 Slides Adapted from Cheng, MobiSys.
Comparison of Cell, GPS, and Bluetooth Derived External Data Results from the 2014 Tyler, Texas Study 15 th TRB National Transportation Planning Conference.
Rutgers: Gayathri Chandrasekaran, Tam Vu, Marco Gruteser, Rich Martin,
1 Given the following data, compute the tracking signal and decide whether or not the forecast should be reviewed.
How Self-funding Works. Fully Insured 100% Non-refundable Premium Partial Self-funding Administration Stop Loss Premiums Potential Claims (Opportunity.
Snooping Keystrokes with mm-level Audio Ranging on a Single Phone
Cell Phone Traffic Data Technology Demonstration in Minnesota ITS America 2007 Annual Meeting & Exposition Bernie Arseneau, Mn/DOT Rashmi Brewer, Mn/DOT.
Guess the average MONTHLY cost of a one bedroom apartment in Southern Orange County.
Southern California Job Growth Trends Southern California Total San Diego County Orange County Riverside/San Bernardino Counties (The Inland Empire) Los.
Brandon Robinson Danut Tabacaru Victor Ho Autonomous Spacecraft Impact Monitoring and Repair Autonomous Spacecraft Impact Monitoring and Repair.
Pre – bid Meeting 28 July 2004 Council for Development & Reconstruction UTDP – On-Street Parking Management Program Lebanese Republic Council for Development.
Accuracy Characterization for Metropolitan-scale Wi-Fi Localization Yu-Chung Cheng (UCSD, Intel Research) Yatin Chawathe (Intel Research) Anthony LaMarca.
1 Given the following data, calculate forecasts for months April through June using a three- month moving average and an exponential smoothing forecast.
A Study of Smartphone User Privacy from the Advertiser's Perspective Yan Wang 1, Yingying Chen 1, Fan Ye 2, Jie Yang 3, Hongbo Liu 4 1 Department of Electrical.
FPL Energy Wind Index May FPL Energy Wind Index Rolling 15 months, current portfolio 1 1 Average wind speed for the period from those reference.
Presenter: Ailane Mohamed Toufik Authors : Jie Yang †, Simon Sidhom †, Gayathri Chandrasekaran ∗, Tam Vu ∗, Hongbo Liu †, Nicolae Cecan ∗, Yingying Chen.
Data I.
Dejavu:An accurate Energy-Efficient Outdoor Localization System SIGSPATIAL '13.
Speed Speed describes how fast an object is moving Speed describes how fast an object is moving If an object is not moving it has no speed If an object.
College poster project
Series 13 Regional Growth Forecast
Personalized College Profile
Process Costing and Hybrid Product-Costing Systems
2017 Economic Outlook IREM Los Angeles
1) 43 mph to ft/sec 2) 16 days is how many minutes?
Cushman & Wakefield of California, Inc. License #
Accuracy Characterization of Cell Tower Localization
Semester Projects Crash Analysis Reports (Three Reports, 75 points each. Due on February 23, March 23 and April 20). Plus one bonus opportunity. Must.
Think of how a house is divided into separate rooms.
Urban Economics Economics generally studies how markets work
Introduction to Key LTE TDD Features: Beamforming
Accuracy Characterization of Cell Tower Localization
Semester Projects Crash Analysis Reports (Three Reports, 75 points each. Due on March 10, April 14 and May 12). Plus one bonus opportunity. Must attach.
October 20, 2017 Providence St. Joseph, Burbank
February 12 – 19, 2018.
Types of Regions What is a region? What makes a Region?
University Budget and Marginal Cost Components
No Swimming The Saturday Evening Post, June 4, 1921 (cover) 1921 Oil on canvas 25 1/4 x 22 1/4 in. The Norman Rockwell Museum at Stockbridge (Massachusetts)
Most populous state 1 out of every 8 Americans a Californian
Administrative Activities Program Update
While Q Marked Significant Improvement in New Home Sales in Most SoCal Counties; New Home Sales Activity in Q2 Stall in Most Counties.
GABRIELINO By Victor.
Accuracy Characterization of Cell Tower Localization
Semester Projects Crash Analysis Reports (Three Reports, 75 points each. Due on October 1, November 5 and December 3). Plus one bonus opportunity. Must.
זכויות סוציאליות.
Robot Biconnectivity Problem
Boundary Surveys 1.
Section 2.3 Subtracting Integers.
Accuracy Characterization of Cell Tower Localization
In This Week’s “The EDGE”
Histogram-Based Density Discovery in Establishing Road Connectivity
Anesthesia Specialist in Pasadena
Deciphering Pancreatic Islet β Cell and α Cell Maturation Pathways and Characteristic Features at the Single-Cell Level  Wei-Lin Qiu, Yu-Wei Zhang, Ye.
Visually Analyzing Latent Accessibility Clusters of Urban POIs
Presentation transcript:

Accuracy Characterization of Cell Tower Localization Jie Yang†, Alexander Varshavsky‡, Hongbo Liu†, Yingying Chen†, Marco Gruteser♯

Data Description We obtained access to a wardriving trace that covers three areas in the greater Los Angeles area. The Downtown trace covers an area of 3.5km×4.2km in the downtown Los Angeles. The Residential trace covers an area of 6.3km×17km in the southern part of the Los Angeles County. The Rural trace covers an area of 35.4km×36km in the Victor Valley of San Bernardino County.

Data Description The wardriving trace was collected over a period of 2 months in February and March of 2009. The GSM signal strength measurements and their locations were recorded every 2 seconds and the speed of the car averaged about 32kmph. In total, we have 2,613,465 received signal strength (RSS) readings from 105,271 unique locations, resulting, on average, in 24.8 RSS readings from different cells per location. Each cell tower has 2, 3 or 6 cells attached to it, depending on the characteristics of the area and the coverage requirements. We know which cells belong to which cell tower and the actual location of each cell tower.