Location calculation with ML for wifi RSSI signal
Budget: $250 – $750 USD
In this project, you will develop ML algorithm for location calculation for RSSI signals coming from Access points.
I will provide you sample signals for ML algorithms to calculate actual signal positions.
(It is necessary to calculate the location of a phone with the signals received from the Access Points(RSSI) placed at certain locations in indoor. In order to feed the system, sample rssi signals collected from indoor will be shared a list with you. Using these signals, the location can be calculated by using ML techniques.) The algorithm has to provide 1m accuracy for locations.
Example Access Point Definitions:
AP, Floor Langtitude, Longtitude
AP1, 1 41.112491, 29.298048
AP2, 1 41.111652, 29.304504
AP3, 2 41.113330, 29.292928
Sample data from indoor
Device, Floor Langtitude, Longtitude, AP, Rssi
Android-1, 1 41.111736, 29.298939 AP1, -50
Android-1, 1 41.111736, 29.298939 AP2, -85
iPhone-1, 2 41.112605, 29.300455 AP1, -85
I will provide you sample signals for ML algorithms to calculate actual signal positions.
(It is necessary to calculate the location of a phone with the signals received from the Access Points(RSSI) placed at certain locations in indoor. In order to feed the system, sample rssi signals collected from indoor will be shared a list with you. Using these signals, the location can be calculated by using ML techniques.) The algorithm has to provide 1m accuracy for locations.
Example Access Point Definitions:
AP, Floor Langtitude, Longtitude
AP1, 1 41.112491, 29.298048
AP2, 1 41.111652, 29.304504
AP3, 2 41.113330, 29.292928
Sample data from indoor
Device, Floor Langtitude, Longtitude, AP, Rssi
Android-1, 1 41.111736, 29.298939 AP1, -50
Android-1, 1 41.111736, 29.298939 AP2, -85
iPhone-1, 2 41.112605, 29.300455 AP1, -85
Related categories:
Business, Accounting, Human Resources & Legal
Python
Android
Algorithm
Geolocation