Social Distancing Detector system has not any specific objective. Indeed the success of social distancing measures that are implemented over an extended period may depend on ensuring that people maintain social contact from a distance. Some other objectives are. Maintain social distance between peop
Social distancing detector
Social Distancing Detector system has not any specific objective. Indeed the success of social distancing measures that are implemented over an extended period may depend on ensuring that people maintain social contact from a distance. Some other objectives are. Maintain social distance between people. Detecting the People violating the rule of social distance Highlighting the people that are violating
Main objective of Social Distancing Detector as follows:
• To provide a system with a user-friendly environment which is simple to understand and efficient to use.
• To provide a complete solution to he social distanceing situation and monitor peoples movement.
• With the help of this solution we can reduce close contact, and thereby reducing the spread of a contagious diseases.
• With the help of AI it will dectects people movement / activity. Which will be helpful to contain various diseases.
We used different techniques such as deep learning ,OpenCv along with deep neural network COCO dataset and YOLO v3 object detecrion algorithms.
Our implementation method start with the image processing of live streaming frames per seconds are processed and trained model with different data set recognize the faces with and without mask and determine whether the distance among each human is 6 feet , 2 meter or not.
Our proposed software is used to control the spread of contagious diseases. as the name suggests, social distancing implies that people should physically distance themselves from one another, reducing close contact, and thereby reducing the spread of a contagious disease (such as corona virus). Social distancing is crucial to preventing the spread of disease. Using computer vision technology based on OpenCV and YOLO-based deep learning we are able to estimate the social distance of people in video streams. Once an object is detected, classification techniques can be applied to identify a human on the basis of shape, texture or motion based features. In shape-based methods, the shape related information of moving regions such as points, boxes and blocksb are determined to identify the human
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Hd surveillance cameras | Equipment | 4 | 10000 | 40000 |
| Alaram | Equipment | 1 | 5000 | 5000 |
| Sensors | Equipment | 1 | 20000 | 20000 |
| Printing posters | Miscellaneous | 1 | 1000 | 1000 |
| Switches,battery and devices | Miscellaneous | 3 | 3000 | 9000 |
| Total in (Rs) | 75000 |
This project aims to develop an online intranet SIBA CMS (Campus Management System) 2.0 Mo...
This project is to develop a system which would be able to detect the traffic sign board o...
The project is about transforming a mobile phone into an hearing aid. Moreover, a sta...
We are making 3D printer using Arduino. Project Objectives (less than 2500 characters)
Pakistan is facing electricity shortage because of increasing population, modernized home...