/Human-Activity-Recognition-using-Smartphone

This project senses human activity with the help of an app installed in the smartphone which uses ML to predict from the data collected from sensors present in the phone. This project is handled by the DSC ML Team of NIT Patna

Primary LanguageJupyter Notebook

Human Activity Recognition using Smartphone

Introduction:-

This project senses human activity with the help of an app installed in the smartphone which uses ML to predict from the data collected from sensors present in the phone. This project is handled by the DSC ML Team of NIT Patna

Which Sensors we use to get the data:-

  1. Accelerometer

  2. Gyroscope

How it works?

Once we collect the data we will be preprocessing the data and train it using LSTM or further more advanced models. Then finally we would be predicting the activity.

Activities It Tracks:-

  1. WALKING
  2. WALKING_UPSTAIRS
  3. WALKING_DOWNSTAIRS
  4. SITTING
  5. STANDING
  6. LAYING

Tasks Involved:-

  1. Firstly we need to make a android app and integrate with firebase for collecting the data
  2. Then we need to preprocess the data
  3. Create a ML Model
  4. Need to deploy the model in Mobile
  5. Make it avalaible in Playstore

Maintainers of this Project:-