Mohammed Farhan Khan

Mohammed Farhan Khan

Web Development Intern

location of Mohammed Farhan KhanNorth Ryde, New South Wales, Australia

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  • Timeline

  • About me

    Full Stack Developer

  • Education

    • S.F.X. Green Herald School

      2014 - 2016
      A levels
    • BRAC University

      2017 - 2020
      Bachelors of computer science Computer Science
    • University of Technology Sydney

      2023 - 2024
      Master's degree Master's of IT (Software Engineering)
    • Scholastica

      2013 - 2013
      O levels
  • Experience

    • ACI Limited

      Sept 2019 - Nov 2019
      Web Development Intern

      • Developed essential skills for creative web design and frontend development (HTML, CSS, JS)• Gained teamwork skills by collaborating with multiple teams, as it was essential for front endmodeling of websites and digital ad banners

    • TechTrioZ Solutions

      Feb 2021 - Jan 2023
      • Software Engineer

        Aug 2021 - Jan 2023
      • Junior Software Engineer

        Feb 2021 - Aug 2021
    • Omnisystems Network Solutions Pty Ltd

      Aug 2024 - Dec 2024
      IT Engineer
  • Licenses & Certifications

  • Honors & Awards

    • Awarded to Mohammed Farhan Khan
      First place UTS IOS AI Hackathon 2023 - Jun 2023 Developed a prototype model for the platform IOS to detect driver drowsiness for Truckers using swiftUI and an ensemble of classifiers such as Yawn Detection, Eye Detection, Pulse detection with the help of Iphones camera and apple watch. Eye detection: The system utilizes state-of-the-art eye-tracking technology to monitor eye behavior, such as eyelid closures, blink frequency, and gaze direction.Yawn detection: Our driver drowsiness detector employs sophisticated algorithms to detect… Show more Developed a prototype model for the platform IOS to detect driver drowsiness for Truckers using swiftUI and an ensemble of classifiers such as Yawn Detection, Eye Detection, Pulse detection with the help of Iphones camera and apple watch. Eye detection: The system utilizes state-of-the-art eye-tracking technology to monitor eye behavior, such as eyelid closures, blink frequency, and gaze direction.Yawn detection: Our driver drowsiness detector employs sophisticated algorithms to detect yawning patterns, a strong indicator of driver fatigue. By analyzing facial movements and monitoring key facial features, such as mouth and jaw motion, the system can promptly identify signs of drowsiness and issue an alert to the trucker.Heartbeat detection: To enhance the accuracy of drowsiness detection, our system incorporates an innovative heartbeat monitoring component. By incorporating real time data from the health app from apple watch it continuously measures the driver's heart rate. Deviations from a normal heart rate range, indicative of fatigue or drowsiness.With help of all this classifiers drowsiness is detected with OR operation and alert is provided to the driver with sound and vibrations from the apple watch. Show less
    • Awarded to Mohammed Farhan Khan
      Winner of Best Project Award – Software Engineering showcase University of Technology Sydney Jun 2023 Developed and showcased and expanse tracker app with features such as Ai integration to suggest onexpanses, Visual data analytics, OCR recognition from image, pdf generation etc.