A 3D Character is to be created using Blender and then using IOT(Internet Of Things) devices we are to connect the limbs of the human host with the 3D rendered Model using the OpenGL library, which will help us to visualize the movements of the host and enable us to find patterns and movements that
IOT Based 3-D Motion Model Render
A 3D Character is to be created using Blender and then using IOT(Internet Of Things) devices we are to connect the limbs of the human host with the 3D rendered Model using the OpenGL library, which will help us to visualize the movements of the host and enable us to find patterns and movements that may be beneficial for athletes in sports or analyzing the movements of a patient with a skeletal disorientation(s) in real time, these are a couple of applications of our project. The vision that we had when we were selecting this project was to have a system that was diverse enough to be modelled and integrated into any field in the Industry, which may include the following:
The Objectives of the project are stated as follows:
• Fabrication of Motion Tracking Devices.
• Massive amount of Data collection from Sensors with the help of IOT Devices.
• Gait Analysis of the human host is to be done.
• Real time Visualization of Human Body Motion.
• Develop Multiple Applications on gathered data.
There are multiple modules that come together for the Implementation of the projects they are stated as follows:
The Benefits of the Project include:
Make Motion capture technology, using Node MCU(esp 8266) and Accelerometer(mpu-9250) for getting real time values and motion sensors (accelerometer). Dataset shall be obtained from motion of the human host by using motion sensors i.e.(accelerometer) which are to be connected to host’s limbs so that analysis may be done. Stored dataset in database will be mapped with raw skeletal model by using OpenGL library. Model will able to mimic the motion of human host, afterwards a 3D model may be generated and Integrated with previously built on data. Lastly,we will train our model through machine learning which shall enhance the performance of model.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| MPU-9250 Accelerometer | Equipment | 17 | 750 | 12750 |
| ESP-8266 Node MCU | Equipment | 17 | 650 | 11050 |
| Solderless Breadboard | Equipment | 17 | 110 | 1870 |
| 9-Volt Battery | Equipment | 34 | 50 | 1700 |
| 9-Volt Battery Clip | Equipment | 17 | 15 | 255 |
| Casing | Equipment | 17 | 160 | 2720 |
| Jumper Wires | Equipment | 4 | 140 | 560 |
| Double Sided Stickon | Equipment | 1 | 250 | 250 |
| Total in (Rs) | 31155 |
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