Author/Authors :
hazar, manar joundy university of al-qadisiyah - college of computer science and information technology, Qadisiyah, Iraq , shaker, bassam noori university of al-qadisiyah - college of computer science and information technology, Qadisiyah, Iraq , ali, lafta raheem general directorate of education of salahuddin governorate, Iraq , alzaidi, esraa raheem university of al-qadisiyah - college of computer science and information technology, Iraq
Abstract :
The techniques of triangulation in Euclidean geometry can be considered the base of a wide range of positioning techniques for sensor networks; where they deduced the sensor locations by using its geometrical characteristics. This work presents a completely different method based on machine learning, where the data is obtained directly from the natural coordinate systems through the readings provided by Bluetooth Low Energy Devices. The known locations of beacon nodes in the network and the Received Strength Signal Indication (RSSI) can be exploited to detect the current position on mobile device based on the Bluetooth technology.
Keywords :
Neural Networks , Localization , iBeacon , Received Strength Signal Indication , Precision
