Social Distancing by the Thousands: How Our BT710 Makes it Easy

Fri, 07/17/2020 - 13:42

A Public Health Crisis in the Age of Smart Solutions

When COVID-19 emerged as a pandemic this Spring, governments around the world met the news and the challenge in many different ways. Approaches to limiting infections have been driven by known disease vectors for COVID-19, and while there’s still more to learn about the behavior of the virus, one of the most common methods of attempting to limit the spread has been to encourage widespread social distancing.

The principle behind social distancing is clear and simple: since the COVID-19 virus appears to spread primarily through person-to-person contact, keeping a safe distance from others (in addition to secondary measures like face masks) has been shown to have a profound impact on virus spread. And since the virus doesn’t survive well on hard surfaces, eliminating this main vector of spread is enough to dramatically slow infections and results in better outcomes for public health.

Another strategy is contact tracing, which means attempting to reconstruct thef contacts made by a person who has become infected. While effective, it’s often very difficult to build a reliable timeline of who an infected person has been exposed to. People aren’t necessarily able to recall everyone they’ve been around and may not be aware in the first place.

However, as more governments, schools, workplaces, and others explore options for resuming public life in shared public spaces, it has also become obvious that human error and indoor environments make it difficult, if not sometimes nearly impossible, to consistently practice the caution needed to produce those results. As with so many other problems like this, the best and most reliable solutions lie within the realm of the Internet of Things (IoT) – Laird Connectivity's Sentrius™ BT710 wearable tracker/multi-sensor, which is based on Zephyr RTOS, is a great way to automate and simplify the challenges of social distancing and contact tracing.