SALAT POSTURES DETECTION USING AI

Abstract

Salat is the second pillar of Islam. In the Muslim community, it is the most essential and fundamental worshiping activity that believers have to perform five times a day. Salat consists ofseveral postures to perform with accuracy and needs to be performed in a defined sequence. Besides spirituality, Salat has many benefits and welfares. During learning many youngsters are hesitant to correct their postures or sometimes they are unaware of mistakes, even elderly people have several physical constraints and a very common issue ofremembering the sequence, count, and correct posture of Salat poses. Our current project is an Artificial Intelligence (AI) based solution for correct posture detection which can be used for all ages. As a methodology, we have evaluated two modes or methods: The MediaPipe approach which employs a multi step detector machine learning pipeline that has been proved to work in our Media Pipe Hands and Media Pipe Face Mesh products. The pipeline initially locates the person/pose region-of-interest (ROI) within the frame using a detector. Using the ROI cropped frame as input, the tracker then Forecast the pose landmarks and division mask in between the ROI and another method is Convolutional Neural Network (CNN) both ways have given us 99 to 100 % accuracy and promising result with real-time evaluation.