LoK8me — Indoor Location — Android using WiFi Trilateration Technology Project 2015

Final Year Project 2015
Aims
Develop a smartphone application to help locate people in a building in the event of an Emergency.
Overview of experiment
Test Area
Rendered test map to work with the device.
6 Wi-Fi Access Points
(Test Area)
1 Samsung Galaxy Tab 3
(Running the Software)
Amazon Cloud
(1 VPC, 2 Subnets, 1 Web Server, 1 Database)
1 Dell Inspiron 15 Laptop
(Analyse Data Visually, Tables and Graphs)
Lok8Me
Testing Fingerprint Algorithm — Live Environment.
Trilateration
Fingerprinting
Ekahau Site Survey
Overall Test and Results
Test Results
The Path Loss Exponent
Path loss, reduction of power (attenuation) as it propagates through space
Influenced by the environment, walls, steel distance between transmitter and receiver
One Meter Reads
Map 2025 m2, Custom View 800px by 800px
Map
Custom View
Calculate location of APs on UI
Custom View Grid 20X20, 40px each
45 / 20 = 2.25m, 800 / 45 = 17.8 = (1m)
Scan Points for collecting Data
Compared against «Fingerprinting» and «Ekahau»
Average reads from each AP at different locations
15 Locations (A — O)
Trilateration
Indoor Location system for generic Mobile devices using 802.11 Wi-Fi signals
3 Components to calculate results
Future Projects
Sensor Fusion — Integrate of Sensors
Machine Learning / AI — Algorithm, Path loss
Map whole College — Create an Emergency Evacuation APP
Conclusion
Created an Android APP that listened for Wi-Fi signals and estimated a users location.
Built a fingerprint algorithm.
Built Amazon Cloud infrastructure to manage data.
Built a dynamic website to visualize data in table and charts.
Android, AWS Cloud Services, XML, Java, Linux, GIT, Bootstrap, Bit-Bucket, PHP, PDO, SSH, JavaScript.
Aims
Reconfigure layout and addition of more Access Points
Data Comms
Indoor Location
Outline
Aims
Experiment
Test Area
Test Results
Video Demo
Conclusion
Questions

Источник