E RAKAT

Often times, while praying we tend to forget what raqat we?re on no matter how hard we?re focusing. With E-Raqat it will no longer be a problem. E-RAQAT is a device developed to aid concentration in prayers. It will be a smart portable device that could be worn during prayer to count the number of t

Project Title

E RAKAT

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

Often times, while praying we tend to forget what raqat we’re on no matter how hard we’re focusing. With E-Raqat it will no longer be a problem. E-RAQAT is a device developed to aid concentration in prayers. It will be a smart portable device that could be worn during prayer to count the number of the raqats. The internal working is made possible by employing a gyroscope which measures angular velocity and accelerometer which measures linear acceleration. These both are combined to implement motion sensing techniques taking data from the movements and motions in the prayer thus detecting the raqat you are on. The readings from both these will be taken through microcontroller Arduino and imported via Bluetooth to MATLAB/PYTHON. Further techniques of machine learning will be used to process the data and do the actual detection process. It caters to a wide demographic since the problem being addressed is one that almost everyone faces at one point or another. It could prove more helpful for older people or people with memory issues. It’s a budget friendly device so it’ll be easier for the general public to get their hands on.

Project Objectives

• Sensor MPU 6050  used to measure position, angle and fields & then data extracted and acquired through Bluetooth HC-05.
• Data transferred to Arduino IDE Software for gathering run time values from the sensor.
• Data transferred to software Teraterm via bluetooth module.
• Data transferring to Python/MATLAB for further processing.
• Techniques of Machine Learning based on Classification are used7 for result compilation to be used in hardware assembly.

Project Implementation Method

•MPU6050 Sensor used to measure position, angle and fields & then data extracted and acquired through Bluetooth HC05 all connected to Arduino Nano.

•Data transferring using Teraterm software.

•  Machine Learning algorithms used to for result compilation to be used in hardware assembly.

Firstly Arduino Nano was set up with a 5V battery and connected to Bluetooth HC-05. The Arduino was programmed through Arduino software as to record readings in term of pitch, roll and yaw using run time values from Accelerometer in HC-05

The data was then imported using Tera term using Bluetooth and was stored in CSV format

The data collected was treated under different MACHINE LEARNNIG algorithms.

Since our problem is a classification problem so multiple techniques were applied:

 Naïve Bayes                   83%

 Random forest                92%

 Regression Classifier       50%

 
K-Neighbor Classifier     93%

Benefits of the Project

 Our product is unique in the sense that it has no local market competition yet. It is  innovative technology and some products that are similar to it exist only in international market.

 Competitive Advantages include:

1.Portable

2.Innovative

3.User-friendly

 Our product help(s) all age groups, particularly elder people who want to pray five times a day without any distractions by wearing our portable device.

Technical Details of Final Deliverable

•MPU6050 Sensor used to measure position, angle and fields & then data extracted and acquired through Bluetooth HC05 all connected to Arduino Nano.

•Data transferring using Teraterm software.

•  Machine Learning algorithms used to for result compilation to be used in hardware assembly.

Firstly Arduino Nano was set up with a 5V battery and connected to Bluetooth HC-05. The Arduino was programmed through Arduino software as to record readings in term of pitch, roll and yaw using run time values from Accelerometer in HC-05

The data was then imported using Tera term using Bluetooth and was stored in CSV format

The data collected was treated under different MACHINE LEARNNIG algorithms.

Since our problem is a classification problem so multiple techniques were applied:

 Naïve Bayes                   83%

 Random forest                92%

 Regression Classifier       50%
K-Neighbor Classifier     93%

Final Deliverable of the Project

Hardware System

Core Industry

Others

Other Industries

IT

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com