A robot has been created by scientists that ensures people indoors adhere to social distancing rules.
University of Maryland researchers created a machine using thermal imaging and CCTV cameras to detect if anyone is sick or not.
These cameras can monitor crowds. They will detect when people have been close enough for them to break protocol and possibly inform them.
They hope that the surveillance can be used to assist health personnel in contact tracing, and organizers of indoor events who need help controlling people and making sure they comply.
Maryland researchers created a robot to use CCTV cameras to identify people who are violating Covid’s social distancing guidelines. The system is expected to aid in the tracking of contacts. Photographed: The thermal imaging scan of the surveillance program’s trials
Officials can notify individuals if they detect a violation of social distancing and inform them that it is unsafe. Frozone, which is a tiny, autonomous robot, can be used to alert a group. It displays a message on the screen and drives up to people to let them know they have violated social distancing guidelines. Pictured are a group of people who have broken social distancing protocols (top) and Frozone’s reaction (bottom).
The findings of the researchers were published in PLOS One on Wednesday by PLOS.
The cameras can detect when people are standing close to each other for extended periods of time.
These are known as “breaches” because they infringe on social distancing rules.
The system will respond to a breach when it is discovered.
You can simply ask nearby TVs, or monitors to display a reminder about social distance and a public health message.
However, researchers also created a complex reminder system to make people adhere to the rules.
Frozone is a small robotic robot that can be driven to an infracting group by a monitor and cameras.
Frozone works by itself and notifies groups that break protocols and then tells them to get out.
For contact tracing purposes, researchers also discovered how to make certain areas of people more cohesive.
This system distinguishes between interactions which would or would not be considered close contacts by the existing Covid guidelines.
For example, two people walking by one another will not be recognized as close contacts because they had minimal interaction.
Two people walking together, but not moving at the same time, will be regarded as contacts if they stay near one another for an extended period.
The system detects when someone is walking near each other and does not consider this close contact. It also places two people (bottom left), who have walked together for an extended time in the same group. People who are often seated together for extended periods can be grouped by the system (right).
As close friends, people who stay near one another for a prolonged period of time (usually more than 15 minutes) will often be congregated together.
Public health professionals can benefit from this type of clustering.
If a person within a cluster is positive for Covid they may quickly inform others and notify them to take precautions and get tested.
You can also extend the notification to include secondary risks, notifying those who are at higher risk of being exposed that they were part of the same cluster.
However, the system isn’t perfect.
The system cannot detect whether someone is in the same house or not. Therefore, two persons who live within 6 feet of one another may be subject to an unneeded public health notice.
Some people may not like the system. The robot will also notify them automatically. This team hopes to make human-robot interactions more pleasant in the future.