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A neural network-based visible light communication indoor positioning system for moving users / Wafaa Sayed Ebrahim Ahmed ; Supervised Khaled Mohamed Fouad Elsayed , Tawfik Ismail Tawfik

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Wafaa Sayed Ebrahim Ahmed , 2020Description: 73 P . : charts , facsmilies ; 30cmOther title:
  • نظام تحديد المواقع داخل المبانى بإستعمال إتصالات الضوء المرئى و الشبكات العصبية الصناعية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics and Communications Summary: In this thesis, we present an indoor visible light communication (VLC) system to estimate the position of a moving user. This system uses two approaches based on received signal strength, trilateration estimation and neural network estimation. In VLC system, each transmitter sends its position information via light. A photo-detector receiver supported with the moving user is used to receive the transmitted power from each transmitter. The position of the receiver is calculated by using trilateration estimation and neural network estimation. In our study, we consider the two cases, the case of line of sight (LOS) and Non-Line of Sight (NLOS). In case of the receiver normal is not parallel to the transmitter normal, the results showed that trilateration approach gives an error of 18 cm (94% accuracy) while, Neural Network approach offers more accurate positioning with 14cm error (95.3% accuracy) for trained data and 16 cm error (94.6% accuracy) for untrained data.
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.08.M.Sc.2020.Wa.N (Browse shelf(Opens below)) Not for loan 01010110082667000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.08.M.Sc.2020.Wa.N (Browse shelf(Opens below)) 82667.CD Not for loan 01020110082667000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics and Communications

In this thesis, we present an indoor visible light communication (VLC) system to estimate the position of a moving user. This system uses two approaches based on received signal strength, trilateration estimation and neural network estimation. In VLC system, each transmitter sends its position information via light. A photo-detector receiver supported with the moving user is used to receive the transmitted power from each transmitter. The position of the receiver is calculated by using trilateration estimation and neural network estimation. In our study, we consider the two cases, the case of line of sight (LOS) and Non-Line of Sight (NLOS). In case of the receiver normal is not parallel to the transmitter normal, the results showed that trilateration approach gives an error of 18 cm (94% accuracy) while, Neural Network approach offers more accurate positioning with 14cm error (95.3% accuracy) for trained data and 16 cm error (94.6% accuracy) for untrained data.

Issued also as CD

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