Social distance detection

1. A
K
Project title :

2. K.RAJ KUMAR (19TQ1A0526)
B.GANESH (19TQ1AO545)
M.SURESH (19TQ1A0524)

3. ABSTRACT
 COVID-19 has completely changed the world’s view on
pandemics with direct consequencies to global health
and economy.
 During this ongoing COVID-19 pandemic,many
governments have implemented various social distancing
measures such as travel restrictions ,border
control,closing public places and warning the citizens to
keep 1 meter distance from each other .

4. ABSTRACT
 To ensure social distancing protocol in public places and
workplace, the social distance detection tool that can
monitor if people are keeping a safe distance from each
other by analyzing real time video from the camera,
Monitoring People at workplaces, factories, shops.
 we can integrate this tool to their security camera
systems and can monitor whether people are keeping a
safe distance from each other or not.

5. INTRODUCTION
 To limit the spread of an infectious disease, for instance, Covid-19, is
to practice social distancing.
 This is not a new concept, as most societies have been aware of the
value of keeping away from people who are suffering from an infection
for many generations.

6. INTRODUCTION
 A video stream or an image is fed as an input to our self developed
model named Socialdistance tool. The people are detected as
maintaining social distancing or not depending on the distance
maintained between two individuals. They are marked in frames of
different colours and also labels are marked for each of them.

7. SOFTWARE REQUIREMENTS
 Programming language: Python
Libraries
Opencv
numpy
Argparse

8. HARDWARE REQUIREMENTS
• Surveillance Camera
• Recommended computer configuration
Processor (CPU): Intel Core i5 (sixth generation or newer) or
equivalent
Operating System: Microsoft Windows 10 Professional x64
Memory: 8 GB RAM
Storage: 500 GB internal storage drive

9. LITERATURE SURVERY
 Author-Dongfang
Proposed an active surveillance system to show the speard of COVID-
19 by warning individuals in a region of interest.
 Author-R Jhon
Those paper presents, social distancing reduces the risk of people
becoming infected with the novel coronavirus (SARS-CoV-2).

10. EXISTING METHOD
 In the current scenario the only system having to maintain the social
distance in public places is surveillance system like cctv which has to be
monitered by the human which is tedious process for a person to this
task.
 In the existing system there is no such surveillance methods to maintain
the social distance in public places like malls , restaurents , streets ,
education institutions and corporate offices.

11. PROPOSED SYSTEM
 The proposed system focuses on how to identify the person
on image/video stream whether the social distancing is
maintained or not with the help of computer vision and
deep learning algorithm by using the OpenCV.

12. PROPOSED SYSTEM
1. Detect humans in the frame with YOLOv3.
2. Calculates the distance between every human who
is detected in the frame.
3. Shows how many people are at High, Low and Not
at risk.
Objectives:

13. CONCLUSION
We have developed a novel social distancing detector which
can possibly contribute to public healthcare.The model
proposes an Aritifical Intelligence based framework to automate
the process of monitoring the social distancing via object
detection and tracking approaches,where each individual is
identified in the real time with the help of bounding boxes. This
system works very effectively and efficiently in identifying the
social distancing between the people and generating the alert
that can be handled and monitored.

14. DRAWBACKS
ADVANTAGES:
 Limits opportunities to come in contact with contaminated person.
 Provides alerts if specific distance not maintained.
 Provides safety.
 Easy to operate
DISADVANTAGES:
 It requires huge amount of memory to store data.
 Every person may not contain the i5 core.

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