Sensor networks re-imagined

The NSF-funded National Ecological Observatory Network (NEON) was commissioned last year for a likely 3-decade campaign to collect biosphere data across the United States. While some of that data is collected by humans, a lot of the data is automatically sensed and then logged to cyber-infrastructure for later analysis. Another NSF-funded project called SAGE, led by Pete Beckman of Northwestern University (full disclosure, I’m on that team), is working to add AI at the Edge capability to those sensors so that they can be triggered in real time by events such as fire or flood to reconfigure their software for different capabilities.

Meanwhile, there are other things to sense beyond NEON’s current domains: earthquakes, wildfires, and public health emergencies. And there are natural experiments to that lend themselves to adding consequential knowledge to our nation: population gradients from pristine land to urban centers, geo-chemical gradients and different state policy solutions come to mind.

And NEON’s airborne sensor program, currently implemented in human-piloted aircraft, seems to me to be begging to migrate to drones and data-fused with on-orbit sensors like NASA’s OCO2 satellite.

In short, there is much work to be done. And this needs to be built on-top of the infrastructure that already exists–a spiral design scenario. This preserves the considerable set of investments that have already been made, but generates new and better capabilities.