Could AI and Machine Learning be Used to Simplify the Operation Communications Satellite Fleets? | Artificial intelligence
The Massachusetts Institute of Technology has partnered with SES to look into ways artificial intelligence (AI) and machine learning can be used to simplify the operation of their communications satellite fleet.
AI and machine learning could help further Asgardia’s goals of ensuring the peaceful use of space for everyone and building the first space nation with platforms in low-Earth orbit.
During the Satellite Innovation 2018 conference, Valvanera Moreno, SES system architecture and innovation manager, explained that they have an extensive fleet and tens of thousands of telemetry signals on each of their satellites, the next satellites will have even more data to process, which is why they think this sphere has a lot of value.
SES is not the only one looking to use AI to solve various issues. Government agencies and space companies are also looking at ways they can use AI to their advantage.
For instance, Orbital Insight, a geospatial analytics company, depends on artificial intelligence to help answer questions asked by their customers.
Devin Brande, the Orbital Insight advance programs director, explained that Artificial intelligence allows human analysts to extract maximum value from imagery. Brande added that we are on the cusp of mixing modern remote sensing with other sources of intelligence to create a vibrant picture.
Raytheon’s Intelligence Surveillance and Reconnaissance business set up a capability center to focus its artificial intelligence and machine learning expertise. Gabriel Comi, Raytheon Intelligence, Information and Services’ Artificial Intelligence and Autonomy Capability Center chief architect explained that as they grow that into a fundamental capability of their business, the aim is to dissolve the capability center and have it become part of the DNA of their company.
Moreover, CosmiQ Works, a laboratory founded by U.S. intelligence agencies to leverage the innovation of commercial space startups, hosts competitions, known as SpaceNet, that offer cash prizes to competitors who develop automated methods to identify road networks or other landmarks from high-resolution satellite imagery.
CosmiQ then makes the winning algorithms open source. As Adam Van Etten, CosmiQ Works technical director stated, hopefully, that helps our government partners and the commercial sector, but sometimes these algorithms that get a lot of press don’t translate to our domain.
If you’re interested in AI and machine learning especially in relation to space then join Asgardia today and connect with forward-looking people.