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Sri Naga Jahnavi Yeddanapudy
LAWS : Location Accuracy based on Wireless Signals Master Project Defense Sri Naga Jahnavi Yeddanapudy
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LAWS/Sri Naga Jahnavi Yeddanapudy
Outline of the talk Introduction Background Related Work Design Implementation Performance Evaluation Challenges faced Lessons learnt Future Work Conclusion 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS/Sri Naga Jahnavi Yeddanapudy
Introduction Need For Location Accuracy Disaster/Security, e.g. E-911 Better Direction Geo-Fencing Geo-Locking 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Background GPS information – Latitude , Longitude Wi-Fi derived location information Utilize the GPS locations of Wireless access points (AP) BSSID can be used to identify uniquely the signal of an AP. By correlating the strength of three AP signals we can estimate the location of a Wi-Fi receiver. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS/Sri Naga Jahnavi Yeddanapudy
Signal Degrading over Distance and Trilateration Free Space Path Loss - characterizes how the wireless signal degrades over distance (following an inverse square law): Trilateration 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Related Work Improve GPS Positioning Accuracy with Context Awareness [Huang,2008] Our work used only latitude and longitude values not the behavior of the context. Task remainder based on location [Lin and Hung, 2014] Utilized the GPS and Wi-Fi information like the mac address added to the database but not the distances. Validating crowd sensed data using image processing [Talasila, 2013] Our work differs by using GPS and Wi-Fi information. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Location Accuracy Based on Wireless Signals
Assumptions End user must have Android Studio installed to deploy the application. We assume that there are no hackers trying to change or spoof the GPS and Wi-Fi location information. The Android applications that are developed serve the Android smart phones or tablets which have Minimum SDK API 15 : Android (Ice cream Sandwich) LAWS System is provided to Smart phone GPS application for determining the user location. Wi-Fi application for providing the user location based on Wi-Fi and geolocation information. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS Design Design and develop Android app to compute the geolocation info of the receiver based on Google Client API and Location Manager API Design and develop Android app to collect Wi-Fi signals based on Wi-Fi Manager API. Design and develop Trilateration algorithm for calculating the geolocation of the receiver based on the available Wi-Fi signals 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Evaluate Accuracy of Geolocations Computed by LAWS Software
Nine points in UCCS Alpine Soccer Field are chosen 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Implementation LAWS GPS Android Application LAWS Wi-Fi Android Application Location – Geo location -Google Client API Wi-Fi Manager Wi-Fi trilateration Technologies used : Android Studio 1.5 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS/Sri Naga Jahnavi Yeddanapudy
LAWS GPS Application Latitude and Longitude value is determined by using the Location Manager and Google Client CPI 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS Wi-Fi Application
Mac Address of Wifi Base station Frequency in MHz Distance in meters Signal to Noise Ratio SSID 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Geolocation Determined with Wi-Fi Trilateration
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Pseudo code of GPS Smart Phone application
Passing Lat, Lng values Pseudo code of GPS Smart Phone application Adds marker to the map along with lat, lng values 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Pseudo code for Wi-Fi Scan
Distance calculation using Free space path loss Pseudo code for Wi-Fi Scan Scanning of Wi-Fi Base stations Retrieves Mac Address, Signal to noise ratio, frequency, SSID 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Pseudo code for Wi-Fi trilateration
Based on three distances and three Wi-Fi base stations GPS information LAWS/Sri Naga Jahnavi Yeddanapudy 11/14/2018
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Performance Evaluation
GPS Sample for Alpine soccer field Wi-Fi Sample for Alpine center High end Precision data for Alpine center 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Error values 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Average and Variance of nine points with 90 samples
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Average and Variance of nine points
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LAWS/Sri Naga Jahnavi Yeddanapudy
Analysis Results Accuracy of GPS derived geolocation is 75% better than those of Wi-Fi derived information based on the 90 samples that were collected for the Smart Phone Data. Based on the nine values of the smart phones geolocation data, the performance of the GPS is 50% better than the Wi-Fi derived information. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Offset Deviation in Google Earth surprise finding!
Collecting the High Precision Data for these points 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Offset Deviation in Google Earth surprise finding!
Selected locations displayed as Pins by Google Earth 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Difficult Bug in Wi-Fi Code
If the ex, ey ( unit vectors )are not determined properly it doesn’t generate the expected value. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Lessons learnt Wi-Fi API and Google Client API are very useful. Android programming using Android Studio is easy to learn. It is challenging how to develop a user friendly application. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Future work Design and develop E-911 Service Integrate with Geolocation Verification Service. Provide real-time geolocation service 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Conclusion Designed and implemented system for Location Accuracy based on Wireless Signals Provide user location information through GPS Application Provide user location information through Wi-Fi application Conducted experiments to investigate the location accuracy based on Wi-Fi and GPS information and LAWS systems results show that GPS approximately 50% more accurate than Wi-Fi. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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LAWS/Sri Naga Jahnavi Yeddanapudy
References Jiung-yao Huang, Chung-Hsien Tsai, “Improve GPS Positioning Accuracy with Context Awareness”, Ubi-Media Computing, First IEEE International Conference, Pages 94-99, July 31 – Aug Chi-Yi Lin & Ming-Tze Hung, “A location-based personal task reminder for mobile users”, Pages , Personal and Ubiquitous Computing archive, Volume 18 Issue 2, February 2014. Manoop Talasila, Reza Curtmola, and Cristian Borcea, “Improving Location Reliability in Crowd Sensed Data with Minimal Efforts”, Pages 1-8, Wireless and Mobile Networking Conference (WMNC), th Joint IFIP, April 2013. 11/14/2018 LAWS/Sri Naga Jahnavi Yeddanapudy
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Q & A LAWS/Sri Naga Jahnavi Yeddanapudy 11/14/2018
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