Hey, I am
Parth Khanna
I am a Final Year B.Tech Undergraduatestudent developer who loves
building useful and novel hardware
as well as software products.
Let's get to know more about me.
Parth Khanna
I am a Final Year B.Tech Undergraduate
I am pursuing Bachelor Of Technology In Electrical Engineering
at IIT (ISM) Dhanbad.
I love to build softwares and hardware projects.
Currently Learning Web Technologies
When I'm not coding, tweeting or making Insta Filters,
you'll find me playing badminton, chess, singing or with headphones.
Worked in a team of 3. An Application along with a chrome extension from which the teachers can manage students in realtime in an online class being taken on Google Meet. The Application is used to access the attendance and quiz details for both Teacher as well as Student.
Worked in a team of 5 and created a device having a sensor which measures the amount of liquid flowing through a particular cross-section as well the mass of the liquid flown . Using this data an OTP is generated which sent to the owner of the vehicle . Using this OTP the user can view his details from the PetroBYTES Website The website then asks for the amount of petrol that he actually wanted and then calculates the amount of money he has been doped of. The user can next select the address of the petrol pump from the dropdown and submit this data to a database. Using this data We aim to predict the average FLowrate Error and Adulteration for each Petrol Pump using Linerar Regression Model .
Worked in a team of 4. Constructed a wearable wrist band which will record sEMG signals and Accelerometry with the help of sensors such as EMG Muscle Sensor Module and a triaxial accelerometer embedded into the band. Using this information, a Machine Learning algorithm predicted seizures activity and notify the caretaker in case a seizure actually occurs with the help of an Android application.
Face Mask Detection system built using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Thsi face mask detector didn't uses any morphed masked images dataset. The model is accurate.This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19.
