AR for Learning and Teaching

Shriram KV

Shriram KV

Bengaluru, Karnataka

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  • 0 Collaborators

India is a land of rich heritage and culture as all of us know. Rich Vedas and Knowledgeful gurus have already glorified the country with divine knowledge. And, the advancement of the science and technology has also put us in the lime light in the past couple of decades. Still, teaching Biology and human anatomy at the school level is a big challenge for the teachers. Explaining human organs to a 8th grade student is not easy here. Either, the teachers don’t discuss the content or they do it namesake. So, eventually, the students from the lower grades to the higher grades do not have any idea about what they read and it makes the subject and knowledge not up to the mark. For instance, the dos and don’ts of the human anatomy is covered as part of the syllabus, which cannot be completely discussed in the class due to cultural hesitations. Our Solution shall help the learners and teachers we hope! ...learn more

Project status: Published/In Market

Virtual Reality, Artificial Intelligence

Intel Technologies
Intel Python, Intel powered laptop

Code Samples [1]

Overview / Usage

Thanks to the Intel NUC8i7HVK, the formerly Hades Canyon was the savior. Our normal PCs with limited graphics ability and speed was stuck totally while building the application. After the NUC arrived, the process went smooth and all the troubleshooting and development were completed much faster than expected. The speed and elevated graphics support provided by the NUC were the important features to be highlighted. Intel Core-i7 processor with the AMD Radeon RX Vega M GPU was, in fact, awesome and the difference was felt right in the first attempt. Whenever anyone works on AR or VR, the most important factor to be considered is the real-time performance, i.e. the response should be much faster, every time, on time. The delayed response shall keep the users away from the system and we were worried about the same earlier with the simple PC test run. It was delayed and we could feel that difference and technically, it was dead time. NUC has blown that delay out. Wish we port it on to the headset too 

For the development and test bed setup to be visualized, one can refer to the below architecture diagram.

Methodology / Approach

Pl. refer to the flow diagram to understand the approach clearly! It is simple and self-explanatory.

Technologies Used

Leap Motion Sensor
Intel NUC
Unity

Repository

https://youtu.be/-6_cO9OMJrI

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