Deep neural network requires high processing GPUs to implement which are not available to every other person that is why we are implementing DNNs on the embedded system like raspberry pi for the face and mask detection so that we dont need high processing GPUs.
Embedded based monitoring system through DNNs
Deep neural network requires high processing GPUs to implement which are not available to every other person that is why we are implementing DNNs on the embedded system like raspberry pi for the face and mask detection so that we dont need high processing GPUs.
Implementing DNNs on small devices like embedded system for face and mask detection and through that detection we are going to challan that person/student who is not wearing a mask.
we divided our project in 3 parts
1) Implementing already built in face and mask detection through DNNs
2) implementing 1st step with out student body dataset in which our model will train.
3)Challan those students through their emails or portal who is not wearing a masks.
1) We dont need to send the videos or images to the server which contain those GPUs and implemented DNNs.
2)Man labour will be less as we dont need the security guard to check every other student who is wearing masks or not.
3)We will get the embedded device which contain the deep neural network inside it which can perform different tasks regarding computer vision.
1) implementing embedded based monitoring system through DNNs
2) Challan will be generated which student is not wearing a mask.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| raspberry pi 4 1GB | Equipment | 1 | 9500 | 9500 |
| rashberry pi | Equipment | 1 | 4500 | 4500 |
| Total in (Rs) | 14000 |
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