Fatma Eid, Software Embedded systems Engineer

Fatma Eid

Software Embedded systems Engineer

The Egyptian Bureau for Engineering

Lieu
Qatar - Doha
Éducation
Baccalauréat, Engineering
Expérience
11 years, 10 Mois

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Expériences professionnelles

Total des années d'expérience :11 years, 10 Mois

Software Embedded systems Engineer à The Egyptian Bureau for Engineering
  • Egypte - Le Caire
  • Je travaille ici depuis juillet 2014

1.Developing embedded system software for POS (Point Off Sale)
terminals, which cover some of nationals projects and banks
projects also.

2.Developing desktop and windows services for banks.

Projects:
Card data manager application (credit\debit card printing and issuing solution ) that is used in some national banks and non national banks also

Software embedded systems engineer à Smart Cards Application
  • Egypte - Le Caire
  • septembre 2013 à août 2014

Developing embedded system software for POS (Point Off Sale)
terminals, which cover some of nationals projects and banks
projects also.

Projects:
Bread points exchange project, developed and designed the client pos
terminal software (Ministry of Supply and Internal trade - Egypt).

External Public relations à Steps Towards Progress
  • Egypte - Le Caire
  • août 2011 à septembre 2012

1.Publicizing news & events.
2.Promoting established products or services.
3.Creating a favorable reputation of the company.
4.Arranging & publicizing public appearance of marketing spokespersons.
5.Attracting news media coverage of sales conferences, trade shows &other sales promotion events.

Éducation

Baccalauréat, Engineering
  • à Cairo University
  • janvier 2008

2008-2012Faculty of engineering -Cairo University - Egypt • B.Sc. (Electronics and Communication), June 2012 • Graduation Project: Body recognition and Gesture development using Kinect SDK • Graduation Project Grade: excellent • Graduation Grade: Very Good • Elective Courses • OS (operating system) • Wireless communication • DSP Abstract About Graduation Project We propose a new method to quickly recognize the static and moving bodies using Microsoft Kinect sensor that can be used to reliably capture information from body movements in real-time fashion. We capture the measurements from the sensor, classifying them with several classification methods to get the best accuracy. We used Euclidian, City block, Naïve Bayes and Neural Network classifiers which enable us to recognize 30 people with accuracy exceeds 90%.

Specialties & Skills

Embedded Systems
Programming
IT Technical Support
visual studio 2010
Embedded c
Soft Skills:Highly Communications and negotiation Skills
Android

Langues

Arabe
Expert
Anglais
Expert

Adhésions

Resala charity
  • Responsible member in clothes department
  • June 2010

Formation et Diplômes

Behavioral approach course (Certificat)
Date de la formation:
July 2011
GSM course (Formation)
Institut de formation:
IT gate company
Date de la formation:
August 2010
Durée:
30 heures

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