Käyttäjän MTayabKhan profiilikuva
Jäsen alkaen 23. joulukuuta 2016
0 Suositukset


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I am an Electrical Engineer and CEO at ssembeds who loves to work with Raspberry pi development, Computer vision with opencv-python and embedded systems design. The work experience with Rpi, computer vision and python allow me to offer quality work in the fields of single board computing, making standalone systems, desktop applications for booth Rpi and PC, customization of Rpi for special purpose. I am being the head of our technical team who work on making stand alone devices using single board computers to solve real world problems. My personal experience with python is building opencv, numpy, Scipy with hand on experience to solve different data and vision based problems. With Rpi, I have experience with all its interfacing, building required packages, boot it to a specific task and customize it. Clients that are having problems in any of the relevant areas can contact me directly and I am available to discuss their problems and provide a quality solution.
$8 USD/hr
2 arvostelua
  • 100%Suoritetut työtehtävät
  • 100%Budjetin mukaisesti
  • 93%Ajallaan
  • N/AUudelleenpalkkaamisaste


Viimeaikaiset arvostelut



Jul 2018 - Jun 2019 (11 months)

Designation and Role: Incubate/Founder and CEO of Tech Based Startup ‘Smart & Safety Embedded’ at The Catalyst GIKI. The responsibility was technology development of a stand-alone system for Driver’s Safety and Surveillance based on Raspberry pi with computer vision, opencv and system architecture on Linux-python. Other responsibilities contain Generating Progress Reports, Market Surveys and Collaborations.


Electrical Engineering

2013 - 2017 (4 years)


Course on Soft Skills (2018)

COMSATS Institute of Information Science and Technology

The course consist of learning modules on how to improve the soft skills like, Time Management, Stress Management, How to be successful professional, how to be a good human and how to interact and communicate.


Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure

In the proposed method is for a real time scenario where frames are read by computing board on real time which is processed for driver's sleepiness detection and alarm. In a real time frame, The face detection and extraction of driver is lead to classification of sleepy driver and non sleepy driver to generate an alarm. It is implemented on real time stand alone computing board which provide 95% accuracy and 18fps computation speed.


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