The problem Advanced Unconventional Fitness Tracker solves

-> Detects the exercise when the device is in the active-time mode i.e when the code is running. Can currently detect Vertical Raises, Bicep Curls, Push-Ups and Sit-Ups.
-> Detects number of steps and displays total calorie burnt in passive mode.
-> Detects the number of counts a user works out.
-> Also notifies movement accuracy to reduce muscle stress and injuries.
-> Total Model accuracy of 90%.

Challenges I ran into

I had a lot of hurdles with getting the counts right for different workouts since each of their signals(from gyro sensor) had different damping factors to account for. Humorously as it sounds, that was mitigated by using an 'if' loop with different conditions for different workouts.