Then there’s data. Galaxies of it. Ultra-enhanced images with the ability to “see” through cloud and groundcover greatly improve agricultural, environmen tal, meteorological, military, transportation, and logistical operations. Given the rapid expansion of satellite communication webs in support of IoT, the volume of data will continue to explode. Over half-a-million IoT customers already use Iridium satellites to monitor, track, diagnose, troubleshoot, and maintain millions of trains and cargo vessels, along with their associated engines, cranes, platforms, containers, and other devices.
Not to be outdone, SpaceX plans to launch over 4,000 Starlink satellites by the end of 2023, with the ultimate aim of making high-speed internet accessible from anywhere in the world. Already, China’s space station has had to perform two emergency maneuvers to avoid possible collisions with Starlink assets. Finally, the European Space Agency aims to create a digital twin of Earth in order to improve how we monitor and forecast the impact of human activity on our planet.
Coordinating and keeping the myriad moving parts running smoothly require extensive, knowledge-rich AI- and machine-learning-based analytics and decision support technology. As for the processing and storage capacity needed for all of this, cloud providers are already hopping onboard. These include Amazon’s 3,000-plus satellite Project Kuiper and Microsoft’s “Cloud in the Cloud,” aka, Azure Space.
Where no one has gone before
As space-related systems grow in size and complexity, so do the problems. But more knowledge generated and embedded in automated systems, especially AI, translates into more opportunities for KM. These opportunities span the entire space systems lifecycle, from cradle to grave.
The cradle end involves the highly complex processes of design, construction, test, mission planning, and deployment of the satellites and launch vehicles. The grave side deals with critical decisions such as whether to commend a spacecraft’s body to a cold, orbital graveyard or to initiate a fiery, precisely controlled descent back into Earth’s atmosphere.
In between, in addition to ongoing maintenance, massive streams of uplink and downlink data require fast and reliable routing and processing. This includes managing the limited radio frequency spectrum available through which all of that data must pass.
The reach extends far beyond Earth’s orbit, especially given renewed interest in the exploration of the entire solar system, from the sun to the Kuiper belt. Commercial ventures on the drawing board include mining the moon, asteroids, and the moons of Jupiter and Saturn.
Perhaps nowhere are the five V’s of information (volume, velocity, variety, veracity, and value) more pronounced than in the business ecosystem of space. Managing tens of thousands of different types of objects ranging in value from worthless junk to billions of dollars travelling at blinding speeds present a wide-open opportunity for KM. Add human space travelers into the mix, and the problems and challenges multiply even more.
We began this article with a retrospective on predictions made almost 2 decades ago. At that time, many were also predicting the eventual demise of KM. If that happens, it will only be because we have not taken advantage of the need for bringing new knowledge to bear in response to the dizzying amounts of data and complexity being generated, all with the potential to further accelerate both human and machine evolution. And when it comes to commercial space, instead of Yogi Berra, you might try quoting another famous philosopher, saying that if we play our cards right, these opportunities can literally take us “to infinity ... and beyond!”