scholarly journals Smart System to Monitor Social-Distancing During the Covid-19 Pandemic

2020 ◽  
Author(s):  
Omar Elharrouss ◽  
Noor Al-Maadeed ◽  
Khalid Abualsaud ◽  
Amr Mahmoud ◽  
Tamer Khattab ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Computer Vision ◽  
Real Time ◽  
Video Surveillance ◽  
Social Distance ◽  
Moving Objects ◽  
Physical Distance ◽  
Disease Spread ◽  
Smart System ◽  
Social Distancing

We introduce a smart system to track and maintain real-time physical distance between people and to warn people over any deviation from the prescribed distances. Social-distancing is an effective way of slowing infectious disease spread. People are advised to reduce their contacts with each other, thus reducing the chances of transmitting the disease through physical or near contact. We proposed a system to automate the task of tracking social distance using video surveillance and sensors. The system can be used to detect moving objects and measure distance between people. The system collected sensor environmental information for commercial, industrial and governmental purposes. Furthermore we are using drown to detect crowded area. The accuracy of detection using sensors can be helpful when it combined with the camera for computer vision task in terms of visualization using camera and rebuses of detection using sensor. Both camera and sensor gauge the environment to detect moving objects simultaneously.

scholarly journals DETECTION AND TRACKING OF MOVING OBJECTS WITH REAL-TIME ONBOARD VISION SYSTEM

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 67-71 ◽  
Author(s):  
D. Y. Erokhin ◽  
A. B. Feldman ◽  
S. E. Korepanov
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Video Sequence ◽  
Moving Objects ◽  
Vision System ◽  
Unmanned Aircraft ◽  
Computer Vision System ◽  
Geometric Transformations ◽  
Detection And Tracking ◽  
Video Sensor

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

scholarly journals Real Time Tracking RGB Color Based Kinect

2017 ◽  
Vol 11 (3) ◽  
pp. 98
Author(s):  
Ahmed Mustafa Taha Alzbier ◽  
Hang Cheng
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Video Processing ◽  
Background Subtraction ◽  
Moving Objects ◽  
Blue Color ◽  
The Real ◽  
Color Recognition ◽  
Kinect Camera ◽  
Computer Vision Technology

As the present computer vision technology is growing up, and the multiple RGB color object tracking is considered as one of the important tasks in computer vision and technique that can be used in many applications such as surveillance in a factory production line, event organization, flow control application, analysis and sort by colors and etc. In video processing applications, variants of the background subtraction method are broadly used for the detection of moving objects in video sequences. The background subtraction is the most popular and common approach for motion detection. However , this is paper presents our investigation the first objective of the whole algorithm chain is to find the RGB color within a video. The idea from the beginning was to look for certain specific features of the patches, which would allow distinguishing red, green and blue color objects in the image. In this paper an algorithm is proposed to track the real time moving RGB color objects using kinect camera. We will use a kinect camera to capture the real time video and making an image frame from this video and extracting red, green and blue color .Here image processing is done through MATLAB for color recognition process each color. Our method can tracking accurately at 95% in real-time.

scholarly journals Helping the Blind to Get through COVID-19: Social Distancing Assistant Using Real-Time Semantic Segmentation on RGB-D Video

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5202
Author(s):  
Manuel Martinez ◽  
Kailun Yang ◽  
Angela Constantinescu ◽  
Rainer Stiefelhagen
Keyword(s):  
Real Time ◽  
Semantic Segmentation ◽  
Physical Distance ◽  
Assistive Devices ◽  
Prototype System ◽  
Blind People ◽  
Audio Feedback ◽  
Daily Lives ◽  
Social Distancing ◽  
Depth Cameras

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the aim of slowing the spread of the disease, but it is difficult for blind people to comply with this. In this paper, we present a system that helps blind people to maintain physical distance to other persons using a combination of RGB and depth cameras. We use a real-time semantic segmentation algorithm on the RGB camera to detect where persons are and use the depth camera to assess the distance to them; then, we provide audio feedback through bone-conducting headphones if a person is closer than 1.5 m. Our system warns the user only if persons are nearby but does not react to non-person objects such as walls, trees or doors; thus, it is not intrusive, and it is possible to use it in combination with other assistive devices. We have tested our prototype system on one blind and four blindfolded persons, and found that the system is precise, easy to use, and amounts to low cognitive load.

scholarly journals An IoT Based Model to Defend Covid-19 Outbreak

2021 ◽  
Vol 10 (7) ◽  
pp. 152-157
Author(s):  
Deepa Sonal* ◽  
Dina Nath Pandit ◽  
Md. Alimul Haque
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Condition Monitoring ◽  
Social Distance ◽  
Smart Phone ◽  
Healthcare Spending ◽  
The Internet ◽  
Web Based ◽  
Social Distancing ◽  
The Internet Of Things

Covid-19 is a pandemic that has swept the globe since the end of 2019. Scientists are working around the clock to create a vaccine to combat the Coronavirus. People are now monitored using smart-phone and web-based software. The Internet of Things (IoT) refers to items that have sensors embedded in them. To check the spread of Covid-19, the IoT can be used. Social Distancing breaks the chain of spreading. It has an effect not only on healthcare spending but also on the speed at which infected patients recover. IoT can be used efficiently for maintaining social distance. As a result, the current research aims to define, analyze and highlight the inclusive applications of the IoT philosophy by providing a perspective roadmap to combat the COVID-19 pandemic by maintaining social distancing. Reviewing the literature, a real-time detecting and alerting method for the COVID-19 condition monitoring is proposed.

scholarly journals An SIR-type epidemiological model that integrates social distancing as a dynamic law based on point prevalence and socio-behavioral factors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maritza Cabrera ◽  
Fernando Córdova-Lepe ◽  
Juan Pablo Gutiérrez-Jara ◽  
Katia Vogt-Geisse
Keyword(s):  
Social Distance ◽  
Transmission Rate ◽  
Close Contact ◽  
Oscillatory Behavior ◽  
Point Prevalence ◽  
Disease Spread ◽  
Epidemic Outbreak ◽  
Social Distancing ◽  
Small Peak ◽  
Functional Forms

AbstractModeling human behavior within mathematical models of infectious diseases is a key component to understand and control disease spread. We present a mathematical compartmental model of Susceptible–Infectious–Removed to compare the infected curves given by four different functional forms describing the transmission rate. These depend on the distance that individuals keep on average to others in their daily lives. We assume that this distance varies according to the balance between two opposite thrives: the self-protecting reaction of individuals upon the presence of disease to increase social distancing and their necessity to return to a culturally dependent natural social distance that occurs in the absence of disease. We present simulations to compare results for different society types on point prevalence, the peak size of a first epidemic outbreak and the time of occurrence of that peak, for four different transmission rate functional forms and parameters of interest related to distancing behavior, such as: the reaction velocity of a society to change social distance during an epidemic. We observe the vulnerability to disease spread of close contact societies, and also show that certain social distancing behavior may provoke a small peak of a first epidemic outbreak, but at the expense of it occurring early after the epidemic onset, observing differences in this regard between society types. We also discuss the appearance of temporal oscillations of the four different transmission rates, their differences, and how this oscillatory behavior is impacted through social distancing; breaking the unimodality of the actives-curve produced by the classical SIR-model.

scholarly journals Infectious diseases and social distancing in nature

Science ◽  
2021 ◽  
Vol 371 (6533) ◽  
pp. eabc8881 ◽  
Author(s):  
Sebastian Stockmaier ◽  
Nathalie Stroeymeyt ◽  
Eric C. Shattuck ◽  
Dana M. Hawley ◽  
Lauren Ancel Meyers ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Social Behavior ◽  
Infectious Diseases ◽  
Social Interactions ◽  
Disease Spread ◽  
Social Distancing ◽  
Nonhuman Animals ◽  
Underlying Mechanisms ◽  
Induced Changes

Spread of contagious pathogens critically depends on the number and types of contacts between infectious and susceptible hosts. Changes in social behavior by susceptible, exposed, or sick individuals thus have far-reaching downstream consequences for infectious disease spread. Although “social distancing” is now an all too familiar strategy for managing COVID-19, nonhuman animals also exhibit pathogen-induced changes in social interactions. Here, we synthesize the effects of infectious pathogens on social interactions in animals (including humans), review what is known about underlying mechanisms, and consider implications for evolution and epidemiology.

scholarly journals YOLO Based Social Distancing Violation Detection

2021 ◽  
Vol 10 (10) ◽  
pp. 50-51
Author(s):  
Raj Kumar Pal ◽  
Ranjan Keshri ◽  
Sandeep Verma ◽  
Subhomoy Chattopadhyay
Keyword(s):  
Computer Vision ◽  
Social Distance ◽  
Social Distancing ◽  
Advanced Computer ◽  
Vision Technique ◽  
Computer Vision Technique

YOLO Based Social Distancing Violation Detection. Covid 19 can be prevented if few norms are followed properly. Social distancing is one of the important norms to stop spreading COVID-19. Advanced Computer Vision technique can be implemented to identified if few persons are maintaining social distance or not. This can be used to spread awareness.

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