By the time of the 1918 flu pandemic, epidemiology was a little more than a century old, and still considered beside the point when it came to separating life from disease. Not so as the final victim was buried. Data-driven public health policy had arrived as more government and educational institutions implemented disease surveillance.
A similar sudden shift in sentiment toward data and disease could be occurring today with edge-enabled mobile technology. This juxtaposition does not trivialize the suffering imposed by COVID-19 infections. It points out how the polarizing image of electronic surveillance and big data (government and private) could change if policies can demonstrate their efficacy in blunting a pandemic.
Four recent efforts demonstrate how far edge and mobile systems can reach when it comes to monitoring people on the go and recording how close they get to each other. These efforts -some of them part of existing products – could be pointing to a future when watchful systems win greater acceptance among the watched. Or when Western governments impose them with few apologies.
First is Vivacity Labs Ltd., which uses artificial intelligence and Internet of Things sensors to record and analyze traffic. It is part of a two-year trial to see how London’s vehicle traffic can be made safer and lighter.
But last month, it used its setup as well as cameras owned by some municipalities to see how well U.K. citizens are complying with stay-at-home advisories from the government. London subsequently put the nation on lockdown.
Vivacity’s machine-learning algorithms can classify traffic with a fairly high degree of granularity, recognizing and counting everything from pedestrians to articulated buses.
Given that project and the fact that its software already can gauge traffic density, company executives instructed it to see if the message was getting through.
Vivacity found that the advisories cut pedestrian traffic by an underwhelming 30%. They also produced only a one-third drop in pedestrians walking within six feet of each other.
Other traffic was even less affected: Car and motorcycle traffic fell 15% and bicycling dropped by just 13%.
Another vendor effort involved X-Mode Social Inc., a location-data firm, which has partnered with Tectonix GEO, a geospatial data-visualization service. They have teamed to monitor the movements of mobile devices in the United States as a way of tracking people’s movement.
The pair has gained attention for a sobering demonstration video Tectonix GEO executives posted on Twitter showing how far young people traveled after recent Spring Break revelry on a Ft. Lauderdale, Fla., beach. The dispersal of vacationers back to a multitude of cities and states shows the possibility for the spread of the disease.
Facebook also is involved, albeit passively, in a project to monitor mobile devices.
Company executives have begun sharing some of the mountains of data it collects from the majority of its billions of subscribers in a bid to understand COVID-19’s virulence.
An article published by medical news site Stat describes how Harvard University public-health researchers as well as counterparts from Taiwan, Italy, London and elsewhere have been teasing apart the Facebook data. They want to monitor travel, of course, but perhaps more important, researchers want to know how often members encounter one another.
At least some of the Facebook data that researchers have access to comes from its Disease Prevention Maps program for non-profit organizations trying to lessen the likelihood of disease-related suffering.
And, just as scientists think they see indications about how COVID-19 is going to play out, there are signs about how far this health-related surveillance can go.
A U.K. startup last week said it had become a third-party provider of Apple Inc.’s Indoor Maps. Dent Reality executives say they are working on indoor augmented reality navigation.
While Apple has a decent record on protecting its customers privacy, CEO Tim Cook could be possibly persuaded by arguments about the common good, and give up indoor traffic data.
analytics | artificial intelligence | big data | edge computing | IoT | sensors