IMU Based Namaz Khushoo Tracker

Project Title

IMU Based Namaz Khushoo Tracker

Project Area of Specialization Wearables and ImplantableProject Summary

Project Summary:  

Our project title is IMU Based Namaz Khushoo Tracker. This project is inspired by the next generation of wearable gadgets that use an IMU sensor to capture body movements and provide useful data. The project is intended to employ an IMU sensor that captures body movements during Namaz, and then tell its wearer whether the actions performed by him/her are in the correct sequence or not, and therefore would be able to identify mistakes in Namaz. The gadget will employ a real-time vibrator motor attached to the body.    

Our project will Therefore help the Muslims improve the quality of their Namaz. Most people unintentionally miss a particular element or raka'ahs of Namaz or do not give proper time in Rukhoo, Sajda, Qoama, and Jalsa. This device will help in this way to minimize these kinds of errors in Namaz. It will contain the IMU sensor that will be attached to the body. This device captures the real-time data and, based on which it will classify which transition Namaz has performed using a deep learning algorithm. Besides the real-time feedback, the project will also build an Android app that provides a summary of Namaz in the form of a user dashboard. 

Project Objectives

Project Objectives 

We have the aim to achieve the following objectives through this project: 

1. The main objective of this project is that we will make a product that will give us real feedback continuously, we are using the Microcontroller Raspberry pi 4 in it, we will also prepare the module, and if an individual commits an error in Namaz this gadget will help him/her to identify the error. 

2. After doing this project, we will have some expertise in Machine learning, App designing, Microprocessor interfacing, different programming languages like Python, Kotlin, deep learning, etc. 

Project Implementation Method

Project Implementation Method 

We will implement the following methods to achieve the outcome 

1. We will interface the Raspberry Pi with an IMU sensor to visualize the value of the roll, pitch, and yaw from the accelerometer and gyroscope.   

2. We will work on different deep learning and machine learning algorithms to verify which will be best suitable for our project. 

3. We will prepare the dataset of the transitions of Namaz, will train this dataset on the deep learning algorithm, and then deploy it on Raspberry pi.   

4. We will design the Android app using the Kotlin programming language, which will show up all detail of the Namaz. To transmit the information from Raspberry Pi to the Android app running on mobile, we will use a Bluetooth module. 

5. We will work on unity3D to make 3D animation of the body during Namaz and deploy the 3D animation on Android App.  

6. There will be a coin vibrator motor attach to the body for error detection during the Namaz. 

7. We will use the SD card module to store the information. 

Benefits of the Project

Benefits of the Project   

This project will provide the following benefits. 

1. This project will assist to perform Namaz in a better way. It will tell about the missed raka'ahs of Namaz and time reserve in each transition.  

2. It will generate real-time feedback during the Namaz if an error occurs. 

3. It will be small in size and modest in cost.  

4. It will be battery powered which means it is rechargeable and thus durable.

5. It will be easily repairable. 

Technical Details of Final Deliverable

Technical Details of Final Deliverable 

The whole project  comprises of two-parts i.e, 

1. Hardware

2. Software  

1. Hardware: 

The hardware includes the following   

1. IMU Sensor: IMU sensor will provide the data of the body during Namaz. 

2. Raspberry Pi: Raspberry Pi will process the information or data of the IMU Sensor and classify the transition of Namaz.  

3. Bluetooth module: After processing, the output data of raspberry pi will be transferred to the Android app which will be running on mobile or computer. 

4. Vibrator motor: If Raspberry Pi finds some error, it will generate real-time feedback during Namaz.

5. GPU: We will use GPU to train the neural network fastly. 

2. Software  

The software includes following  

1. Android studio: We will be using  Android Studio to design the Android App.  

2. Kotlin: Kotlin programming language will be used to design the Android App. 

3. MATLAB: We will be using MATLAB to train the model of the LSTM (Deep learning algorithm) for classifying the transition of Namaz. 

4. Python: Python language is used mainly to deploy a trained model of LSTM on Raspberry Pi and also to control the raspberry pi. 

5. Unity3D: Unity3d is used to add the 3d animation in the Android App of who will perform the Namaz. 

Final Deliverable of the Project Hardware SystemCore Industry OthersOther Industries Manufacturing Core Technology Artificial Intelligence(AI)Other Technologies Wearables and ImplantablesSustainable Development Goals Good Health and Well-Being for People, Quality EducationRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	51100
Raspberry Pi 4 (Model B, 4GB RAM)	Equipment	1	16000	16000
IMU sensor (MPU-9250)	Equipment	2	750	1500
NVIDIA GeForce GTX 660 GPU	Equipment	1	23000	23000
Bluetooth module (HC-05)	Equipment	1	600	600
box for module, Li-Po Battery, SD Card module, coin vibrator, etc.	Miscellaneous	1	5000	5000
printing, posters, demo setup, etc.	Miscellaneous	1	5000	5000