Applications Of Artificial Intelligence in Space Industry

Applications Of Artificial Intelligence in the Space Industry

Artificial Intelligence is employed in the space industry to foster innovation, to automate construction, and to improve productivity. AI technology has been changing the way satellites are produced and used - it has enhanced manufacturing processes as well as satellite imaging systems, spectrum usage, and telemetry.

Applications Of Artificial Intelligence in the Space Industry

1. Manufacturing

AI is boosting the space industry, in particular the automation of manufacturing processes for space-tech. Satellite manufacturing is laborious and time-intensive. It requires high precision engineering throughout the whole process and the numerous parts that the satellite consists of. Novel AI algorithms and systems can automate some of the more time-consuming tasks such as the cleaning and cutting of satellite parts. Moreover, AI can be used to periodically capture measurements of core components, thus allowing engineers to assess the health and status of the components during the engineering process and to spot potential problems early on. Such automated processes reduce the amount of time that is needed to build a satellite and thus play a major role in the quest to speed up the process of getting satellites ready for launch.

2. Earth Exploration and Satellite Imaging

AI combined with satellite imaging technologies provides powerful tools to enhance the precision of earth exploration and mapping operations. According to estimates by the European Space Agency more than 150 terabytes of data are produced by satellites every day. Thus, AI-based preprocessing of this huge amount of data is a necessity in order to efficiently transmit, process and analyze it.

In terms of applications, earth-imaging data is often used to provide valuable information to both governmental and non-governmental entities, allowing them to assess how the climate change is affecting the earth, to track the migration of certain animals, or to monitor shipping lanes.

3. Operations, Telemetry, and Control

AI is also applied to monitor telemetry data and to provide feedback to satellite operators who may alter the satellite’s trajectory. Moreover, telemetry data is used to design autonomous maneuvering systems. SpaceX, for example, designed a system that will automatically adjust the trajectory of satellites in order to avoid collisions. 

Any powerful (AI-based) software comes at the price of presenting a potential vulnerability to the whole system. With the increasing use of AI applications for satellite navigation and operation tasks, the risk of an attack against these systems is on the rise as well. Attackers could gain control of a satellite and block the signal transmissions or even cause collisions. However, AI also has the power to enhance cybersecurity measures and to increase the resilience of satellite systems to attacks.

4. Dynamic Spectrum Detection and Avoidance

Dynamic spectrum usage constitutes another area of application for AI in the space industry. Dynamic spectrum usage means to alter the portion of the electromagnetic spectrum that is used to transmit information. Interference can occur if too many similar frequencies are used at the same time. Through dynamic spectrum usage and artificial intelligence, a satellite can learn to adapt and to switch frequencies in order to avoid interference. Machine learning algorithms can improve space-to-earth signal transmissions in this way. The currently used Wi-Fi technology operates based on dynamic spectrum access (DSA). A similar system that is  enhanced by AI could be implemented in satellites in the future. 

Dynamic spectrum usage is particularly powerful when applied to geostationary and non-geostationary orbit control. Current attempts to eliminate interference have a tendency to fail and operators of geostationary orbit platforms often report interference from non-geostationary orbit systems. Avoiding such frequently occurring interferences requires extensive coordination between both station types before every transmission. Deep learning algorithms can be used to automate the communication and transmission procedure, thus reducing the amount of interference in satellite networks.

Challenges and Opportunities

There’s a wide range of benefits that AI could provide to society by enhancing the space industry. AI has the ability to automate spacecraft control, coordination, and manufacturing, thus lifting many of the constraints that are currently limiting the industry.  AI can reduce costs and lead to innovation, providing new solutions to avoid collisions with space debris or signal interference. 

AI also has the potential to induce growth in industries adjacent to the space industry. Thanks to AI reducing cost and time-investment, researchers and engineers have more freedom to experiment with applications of their technology outside of the space industry.  

Despite these opportunities, there are numerous challenges that we need to overcome to allow AI to meet its full potential in the space industry. Current regulatory frameworks may prove too restrictive for data transmission in order to provide the required AI input data. To coordinate dynamic spectrum usage, confidential information needs to be shared between operators around the globe to establish reliable avoidance mechanisms. However, international data retention laws may not allow for such data exchanges.

As space satellites begin to transmit and store more and more data, new regulatory hurdles may appear. Most data governance laws are based on the physical location of a data subject within a country’s territory to determine which laws apply. It remains to be seen how governments will handle the retention and transmission of and access to data in space beyond the boundaries of any country. Despite these challenges, artificial intelligence and machine learning have the potential to solve many problems the space industry currently faces.