AI’s Role in Maintaining Social Distance
Social distance does not always come naturally to people. A year ago, it was a term used in social sciences literature; now, it has become a concern that makes everyone feel awkward. As experts state, social distance, coupled with personal sanitation and mask-wearing, is the only way to come near people during the pandemic. Capitalize on one of the critical law enforcement areas of the Covid-19, a new AI technology landscape started to flourish that detects social distance via dynamic tracing.
Amazon is the first one to act on the subject among tech giants. Introducing “Distance Assistance” mid-June, just a few months after the first Covid-19 cases have been announced in the US, Amazon aims to share constant intelligence with their workers on whether they are following the social distancing rule. Distance Assistance gives real-time social distance feedback to anyone entering the 1-meter radius of someone else. The AI interface is entered into the building’s camera footage to help site leaders identify high-risk areas with many people. Amazon is set to make the technology opensource, allowing individuals and businesses to download their distance assistance package for free.
Amazon is not the only company that develops AI for the social distance by entering deep learning algorithms into existing cameras. Ipsotek is one of the leading companies in the field of AI in the UK. They are currently working on incorporating an AI algorithm into 627,727 cameras for 9.3 million residents of London. The technology developed under the Crowd Management program helps detect 1-meter rule violations through the camera field’s real-time view. The algorithm can work by keeping the individuals’ identities private, staying in line with the UK’s current privacy rules.
The three critical Aı technologies used in dynamic tracing algorithms are proximity sensoring, computer vision, location correlation, and contact-tracing.
Proximity sensoring is incorporated into personal smartphones and wearables that can warn the user of possible crowding conditions.
Computer vision uses smart cameras like CCTV to automate occupant counting, wait-time meter, and send alerts when people come too close to each other.
Location correlation on mobile apps gives information on how well people generally following social distancing guidelines through an AI module working on the behind.
Contact-tracing apps send warnings to users when they come in close contact with people with a virus infection or have been near someone who was tested positive.
Social distancing is a simple idea but proves to be hard to achieve. The pandemic conditions made tech vendors realize the value of concentrating on the fields of virtual/physical interactions. The advancements in dynamic tracing strengthen the research for other safety purposes such as fire control and law enforcement monitoring. In a world where surveillance is a must to ensure individuals and society’s safety as a whole, AI in the social distance field yields new possibilities for prevention measures.